Hiroyuki Yoshida, PhD

Director of 3D Imaging Research
Department of Radiology
Massachusetts General Hospital
Associate Professor of Radiology
Harvard Medical School
USA

Biography

Dr. Yoshida received his BS and MS degrees in physics and a PhD degree in Information Science from the University of Tokyo, Japan. He previously held an Assistant Professorship in the Department of Radiology at the University of Chicago. He was a Tenured Associate Professor when he left the University and joined the Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), where he is currently the Director of 3D Imaging Research in the Department of Radiology, MGH and an Associate Professor of Radiology at HMS. He also received two industrial awards on his work on system developments: 2012 Innovation Award from Microsoft Health Users Group and Partners in Excellence award from Partners Health Care. He is an author or co-author of more than 170 journal and proceedings papers and 16 book chapters, an author, co-author, or editor of 14 books, and inventor and co-inventor of seven issued patents.

Research Interest

His research interests include: Computer-aided diagnosis, Quantitative imaging and Imaging biomarkers for the diagnosis of abdominal cancers.

Scientific Activities

HONORS AND PRIZES

• (2000) Cum Laude Radiological Society of North America
• (2002) Honorable Mention SPIE Medical Imaging
• (2002) Excellence in Design Radiological Society of North America
• (2004) Certificate of Merit Radiological Society of North America
• (2006) Certificate of Merit Radiological Society of North America
• (2008) Certificate of Merit Radiological Society of North America
• (2009) Cum Laude Radiological Society of North America
• (2009) Editors Recognition Award for Reviewing with Distinction Radiological Society of North America
• (2010) Excellence in Design Radiological Society of North America
• (2011) Magna Cum Laude Radiological Society of North America
• (2011) Certificate of Merit Radiological Society of North America
• (2012) Innovation Award Microsoft Health Users Group
• (2012) Partners in Excellence Partners HealthCare System
• (2014) Gold medal, CyPos Award Japan Radiology Congress
• (2015) Honorable Mention SPIE Medical Imaging

PROFESSIONAL SOCIETIES/MEMBERSHIPS

• (1989) Information Processing Society of Japan (IPSJ), Member
• (1989) The Institute of Electronics, Information and Communication Engineers (IEICE), Member
• (1990) Association for Computing Machinery (ACM), Member
• (1994) International Society for Optical Engineering (SPIE), Member
• (1996) Institute of Electrical and Electronics Engineers (IEEE), Member
• (1996) American Association on Physicists in Medicine (AAPM), Member
• (2005) Radiological Society of North America (RSNA), Member
• (2005) American Roentgen Ray Society (ARRS), Member
• (2008) International Society and Conference Series on Medical Image Computing and Computer-Assisted Intervention, Member
• (2009) Japanese CT Colonography Society, President

Publications

PEER REVIEWED PUBLICATIONS IN PRINT OR OTHER MEDIA

1. Saito S, Yoshida H, Kunii T. The CrossoverNet LAN system using an intelligent head end. IEEE Transactions on Computers. 1989; 38: 1076-1085. doi: 10.1109/12.30863
2. Yoshida H. Network protocol specification with a visual language. Academic Report of TIP. 1989; 12: 26-50.
3. Yoshida H. Face image synthesis with distributed computing. Academic Report of TIP. 1990; 13: 10-19.
4. Yoshida H, Takahara T. A production system based on the distributed artificial intelligence. Academic Report of TIP. 1991; 14: 13-21.
5. Muto K, Ohno H, Yoshida H, Tsuda M. High speed 3 dimensional reconstruction of medical images based on the optimized granularity. Medical Imaging Technology. 1992; 10: 261-262.
6. Ohno H, Muto K, Yoshida H, Tsuda M. High speed image generation based on the loosely coupled distributed system. Academic Report of TIP. 1993; 15: 10-20.
7. Yoshida H, Doi K, Nishikawa RM, Muto K, Tsuda M. Application of the wavelet transform to automated detection of clustered microcalcifications in digital mammograms. Academic Report of TIP. 1994; 16: 24-37.
8. Muto K, Yoshida H, Tsuda M. Parallelization of the wavelet transform using a loosely coupled distributed system. Academic Report of TIP. 1995; 17: 38-49.
9. Yoshida H, Doi K. Fundamentals of wavelet transform and its applications to computer aided diagnosis I. Japanese Journal of Radiological Technology. 1996; 52: 18-26.
10. Yoshida H, Doi K. Fundamentals of wavelet transform and its applications to computer aided diagnosis II. Japanese Journal of Radiological Technology. 1996; 52: 374-383.
11. Yoshida H, Doi K, Nishikawa RM, Giger ML, Schmidt RA. An improved CAD scheme using wavelet transform for detection of clustered microcalcifications in digital mammograms. Academic Radiology. 1996; 3: 621-627.
12. Zhang W, Yoshida H, Nishikawa RM, Doi K. Optimally weighted wavelet transform based on supervised training for detection of microcalcifications in digital mammograms. Medical Physics. 1998; 25: 949-956.
13. Anastasio MA, Yoshida H, Nishikawa RM, Doi K. A genetic algorithm based method for optimizing the performance of a computer aided diagnosis scheme for detection of clustered microcalcifications in mammograms. Medical Physics. 1998; 25: 1559-1566.
14. Yoshida H. Matching pursuit with optimally weighted wavelet packets for extraction of microcalcifications in mammograms. Applied Signal Processing (Special issue on biomedical signal processing). 1999; 5: 127-141.
15. Nakamura K, Yoshida H, Engelmann R, et al. Computerized analysis of the likelihood of malignancy in solitary pulmonary nodules using artificial neural networks. Radiology. 2000; 214: 823-830. doi: 10.1148/radiology.214.3.r00mr22823
16. Li Q, Kantsuragawa S, Ishida T, et al. Contralateral subtraction: a novel technique for detection of asymmetric abnormalities on digital chest radiographs. Medical Physics. 2000; 27: 47-55.
17. Yoshida H, Keserci B. Bayesian wavelet snake for computer aided diagnosis of lung nodules. Journal of Integrated Computer Aided Engineering (Special issue on industrial applications of the wavelet transform). 2000; 7: 253-269.
18. Masutani Y, Yoshida H, MacEneaney P, Dachman AH. Automated segmentation of colonic walls for computerized detection of polyps in CT colonography. Journal of Computer Assisted Tomography. 2001; 25: 629-638.
19. Yoshida H, Näppi J. Three dimensional computer aided diagnosis scheme for detection of colonic polyps. IEEE Transactions on Medical Imaging. 2001; 20: 1261-1274. doi: 10.1109/42.974921
20. Yoshida H, Masutani Y, MacEneaney P, Rubin D, Dachman AH. Computerized detection of colonic polyps at CT colonography on the basis of volumetric features: pilot study. Radiology. 2002; 222: 327-336. doi: 10.1148/radiol.2222010506
21. Näppi J, Yoshida H. Automated detection of polyps in CT colonography: evaluation of volumetric features for reduction of false positives. Academic Radiology. 2002; 9: 386-397.
22. Yoshida H, Näppi J, MacEneaney P, Rubin D, Dachman AH. Computer-aided diagnosis scheme for the detection of polyps in CT colonography. RadioGraphics. 2002; 22: 963-979. doi: 10.1148/radiographics.22.4.g02jl16963
23. Yoshida H. Registration methods for computer aided diagnosis schemes. Medical Imaging Technology. 2002; 20: 23-28.
24. Yoshida H. Screening of colon cancer with virtual colonoscopy: current status and future potential. Stomach and Intestine. 2002; 37: 1379-1386.
25. Näppi J, Dachman AH, MacEneaney P, Yoshida H. Knowledge guided automated segmentation of colon for computer-aided detection of polyps in CT colonography. Journal of Computer Assisted Tomography. 2002; 26: 493-504.
26. Keserci B, Yoshida H. Computerized detection of pulmonary nodules in chest radiographs based on morphological features and wavelet snakes. Medical Image Analysis. 2002; 6: 431-447. doi: 10.1016/S1361-8415(02)00064-6
27. Yoshida H. Multiscale edge guided wavelet snake model for delineation of pulmonary nodules in chest radiographs. Journal of Electronic Imaging. 2003; 12: 69-80. doi: 10.1117/1.1526496
28. Yoshida H. CAD for the detection of colonic polyps in CT colonography. Medical Imaging Technology. 2003; 21: 34-40.
29. Näppi J, Yoshida H. Feature guided analysis for reduction of false positives in CAD of polyps for CT colonography. Medical Physics. 2003; 30: 1592-1601.
30. Yoshida H, Casalino D, Keserci B, Coskun A, Ozturk O, Savranlar A. Wavelet packet based texture analysis for differentiation between benign and malignant liver tumors in ultrasound images. Physics in Medicine and Biology. 2003; 48: 3735-3753.
31. Dachman AH, Glick S, Yoshida H. CT colonography and colon cancer screening. Seminars in Roentgenology. 2003; 38: 54-64.
32. Yoshida H. Local contralateral subtraction based on bilateral symmetry of chest for computerized detection of pulmonary nodules. IEEE Transactions on Biomedical Engineering. 2004; 51: 778-789. doi: 10.1109/TBME.2004.824136
33. Näppi J, Frimmel H, Dachman A, Yoshida H. Computerized detection of colorectal masses in CT colonography based on fuzzy merging and wall-thickening analysis. Medical Physics. 2004; 31: 860-872.
34. Yoshida H, Dachman AH. Computer-aided diagnosis for CT colonography. Seminars in Ultrasound, CT and MRI. 2004; 25: 419-431.
35. Dachman AH, Schumm P, Heckel B, Yoshida H, LaRiviere P. Effect of reconstruction kernel on conspicuity of polyps in CT colonography. AJR American Journal of Roentgenology. 2004; 183: 1349-1353.
36. Frimmel H, Näppi J, Yoshida H. Fast and robust computation of colon centerlines in CT colonography. Medical Physics. 2004; 31: 3046-3056.
37. Yoshida H. CT colonography with multi-detector CT: feasibility for screening of early colorectal cancers. Early Colorectal Cancer. 2004; 8: 507-514.
38. Yoshida H, Dachman AH. CAD techniques, challenges, and controversies in computed tomographic colonography. Abdominal Imaging. 2005; 30: 26-41. doi: 10.1007/s00261-004-0244-x
39. Näppi J, Frimmel H, Yoshida H. Virtual endoscopic visualization of the colon by shape scale signatures. IEEE Transactions on Information Technology in Biomedicine. 2005; 9: 120-131.
40. Näppi J, Okamura A, Frimmel H, Dachman AH, Yoshida H. Region-based supine-prone correspondence for the reduction of false-positive CAD polyp candidates in CT colonography. Academic Radiology. 2005; 12: 695-707. doi: 10.1109/TITB.2004.837834
41. Frimmel H, Näppi J, Yoshida H. Centerline based segmentation of colon in CT colonography. Medical Physics. 2005; 32: 2665-2672.
42. Perumpillichira JJ, Yoshida H, Sahani DV. Computer-aided detection for virtual colonoscopy. Cancer Imaging. 2005; 23: 11-16. doi: 10.1102/1470-7330.2005.0016
43. Suzuki K, Yoshida H, Näppi J, Dachman AH. Massive-training artificial neural network (MTANN) for reduction of false positives in computer-aided detection of polyps: suppression of rectal tubes. Medical Physics. 2006; 33: 3814-3824.
44. Dachman AH, Dawson DO, Lefere P, et al. Comparison of routine and unprepped CT colonography augmented by low fiber diet and stool tagging: a pilot study. Abdominal Imaging. 2007; 32: 96-104. doi: 10.1007/s00261-006-9044-9
45. Cai W, Harris GJ, Yoshida H. Computation of vesselness in CTA images for fast and interactive vessel segmentation. International Journal of Image and Graphics. 2007; 1: 159-176. doi: 10.1142/S021946780700260X
46. Näppi J, Yoshida H. Fully automated three-dimensional detection of polyps in fecal-tagging CT colonography. Academic Radiology. 2007; 14: 287-300. doi: /10.1016/j.acra.2006.11.007
47. Yoshida H, Näppi J. CAD in CT colonography without and with fecal tagging: progress and challenges. Journal of Computerized Medical Imaging and Graphics. 2007; 31: 267-284. doi: 10.1016/j.compmedimag.2007.02.011
48. Cai W, Holalkere N-S, Harris GJ, Sahani D, Yoshida H. Dynamic-threshold level set method for volumetry of porcine kidney in CT images: in-vivo and ex-vivo assessment of the accuracy of volume measurement. Academic Radiology. 2007; 14: 890-896. doi: 10.1016/j.acra.2007.03.005
49. Yoshida H. Analysis of the effect of computer-aided diagnosis and electronic cleansing on screening CT colonography. Early Colorectal Cancer. 2008; 12: 143-154.
P50. Suzuki K, Yoshida H, Näppi J, Armato III SG, Dachman AH. Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography. Medical Physics. 2008; 35: 694-703. doi:10.1118/1.2829870
51. Cai W, Zalis ME, Näppi J, Yoshida H. Structure-analysis method for electronic cleansing in cathartic and non-cathartic CT colonography. Medical Physics. 2008; 35: 3259-3277. doi:
52. Näppi J, Yoshida H. Adaptive correction of the pseudo-enhancement of CT attenuation for fecal-tagging CT colonography. Medical Image Analysis. 2008; 12: 413-426. doi: 10.1016/j.media.2008.01.001
53. Yoshida H. Influence of computer-aided detection of polyps on screening of colon cancer with CT colonography. IEICE Transactions on Information and Systems. 2008; J91-D: 1730-1743.
P54. Nagata K, Okawa T, Honma A, Endo S, Kudo SE, Yoshida H. Full-laxative versus minimum-laxative fecal-tagging CT colonography using 64-detector row CT: prospective blinded comparison of diagnostic performance, tagging quality, and patient acceptance. Academic Radiology. 2009; 16: 780-789. doi: 10.1016/j.acra.2008.12.027
55. Nagata K, Yoshida H. Effect of screening strategies for colorectal cancer with CT colonography. Intestine. 2009; 13: 119-127.
56. Nagata K, Singh AK, Jagtiani MC, et al. Comparative evaluation of the quality of fecal-tagging in CT colonography-barium vs. iodinated oral contrast agent. Academic Radiology. 2009; 16: 1393-1399.
57. Cai W, Kassarjian A, Bredella MA, et al. Tumor burden in patients with neurofibromatosis types 1 and 2 and schwannomatosis: determination on whole-body MR images. Radiology. 2009; 250: 665-673. doi: 10.1148/radiol.2503080700
58. Tsagaan B, Näppi J, Yoshida H. Nonlinear regression-based method for pseudo-enhancement correction in CT colonography. Medical Physics. 2009; 36: 3596-606. doi: 10.1118/1.3147201
59. Näppi J, Yoshida H. Virtual tagging for laxative-free CT colonography. Medical Physics. 2009; 36: 1830-1838. doi: 10.1118/1.3113893
60. Cai W, Tabbara M, Takata N, et al. MDCT for automated detection and measurement of pneumothoraces in trauma patients. AJR Am J Roentgenol. 2009; 192: 830-836. doi: 10.2214/AJR.08.1339
61. Awad M, Motai Y, Näppi J, Yoshida H. A clinical decision support framework for incremental polyps classification in virtual colonoscopy. Algorithms. 2010; 3: 1-20. doi: 10.3390/a3010001
62. Cai W, Yoshida H, Zalis M, Näppi J, Harris G. Electronic cleansing for non-cathartic CT colonography – A structure-analysis scheme. Radio Graphics. 2010; 3: 585-602. doi: 10.1148/rg.303095154
63. Cai W, Lee J-G, Zalis M, Yoshida H. Mosaic decomposition: an electronic cleansing method for inhomogeneously tagged regions in non-cathartic CT colonography. IEEE Transactions on Medical Imaging. 2011; 30: 559-574. doi: 10.1109/TMI.2010.2087389
64. Cai W, Lee EY, Vij A, Mahmood SA, Yoshida H. MDCT for computerized volumetry of pneumothoraces in pediatric patients. Academic Radiology. 2011; 18: 315-323.
65. Xu Y, Cai W, Näppi J, Yoshida H. Fecal-tagging CT colonography with structure-analysis electronic cleansing for detection of colorectal flat lesions. European Journal of Radiology. 2012; 81: 1712-1716.
66. Zalis ME, Blake MA, Cai W, et al. Diagnostic accuracy of laxative-free computed tomographic colonography for detection of adenomatous polyps in asymptomatic adults: a prospective evaluation. Annals of Internal Medicine. 2012; 156: 692-702. doi: 10.7326/0003-4819-156-10-201205150-00005
67. Cai W, Lee JG, Fikry K, Yoshida H, Novelline R, de Moya M. MDCT quantification is the dominant parameter in decision-making regarding chest tube drainage for stable patients with traumatic pneumothorax. Computerized Medical Imaging and Graphics. 2012; 36: 375-386.
68. Motai Y, Yoshida H. Principal composite kernel feature analysis: Data-dependent kernel approach. IEEE Transactions on Knowledge and Data Engineering. 2013; 25: 1863-1875. doi: 10.1109/TKDE.2012.110
69. Cai W, Kim S-H, Lee J-G, Yoshida H. Dual-energy electronic cleansing for fecal-tagging CT colonography. RadioGraphics. 2013; 33: 891-912. doi: 10.1148/rg.333125039
70. Cai W, Zhang D, Shirai Y, Lee J-G, Kim S-H, Yoshida H. Dual-energy index value of luminal air in fecal-tagging CT colonography: Findings and impact on electronic cleansing. Journal of Computer Assisted Tomography. 2013; 37: 183-194. doi: 10.1097/RCT.0b013e31827bc266
71. Huo Z, Summers RM, Paquerault S, et al. Quality assurance and training procedures for computer-aided detection and diagnosis systems in clinical use. Medical Physics. 2013; 40: 077001. doi: 10.1118/1.4807642.
72. Petrick N, Sahiner B, Armato SG 3rd, et al. Evaluation of computer-aided detection and diagnosis systems. Medical Physics. 2013; 40: 087001. doi: 10.1118/1.4816310
73. Hayano K, Lee SH, Yoshida H, Zhu AX, Sahani DV. Fractal analysis of CT perfusion images for evaluation of vascular heterogeneity change induced by antiangiogenic treatment and prediction of survival in hepatocellular carcinoma. Academic Radiology. 2014; 21: 654-60.
74. Hayano K, Yoshida H, Zhu AX, Sahani DV. Fractal analysis of tumor enhancement on contrast-enhanced computed tomography for the prediction of clinical outcome in HCC patients treated with sunitinib. Dig Dis Sci. 2014; 59: 1996-2003. doi: 10.1007/s10620-014-3064-z.
75. Cai W, Lee JG, Zhang D, Kim SH, Zalis M, Yoshida H. Electronic cleansing in dual-energy fecal-tagging CT colonography based on material decomposition and virtual colon tagging. IEEE Transactions on Biomedical Engineering. 2015; 62: 754-765. doi: 10.1109/TBME.2014.2364837

OTHER PEER-REVIEWED PUBLICATIONS

1. Yoshida H, Doi K, Nishikawa RM. Automated detection of clustered microcalcifications in digital mammograms using wavelet transform techniques. Proc SPIE. 1994; 2167: 868-886. doi: 10.1117/12.175126
2. Yoshida H, Xu X, Kobayashi T, Giger ML, Doi K. Computer aided diagnosis scheme for detecting pulmonary nodules using wavelet transform. Proc SPIE. 1995; 2434: 621-626.
3. Yoshida H, Zhang W, Cai W, Doi K, Nishikawa RM, Giger ML. Optimizing wavelet transform based on supervised learning for detection of microcalcifications in digital mammograms. Proc IEEE International Conference on Image Processing (ICIP95). 1995: 152-155.
4. Yoshida H, Doi K, Nishikawa RM, Giger ML. Computer aided diagnosis in mammography: Detection of clustered microcalcifications based on multiscale edge representation. Proc CAR—Computer Assisted Radiology. 1996: 390-395.
5. Katsuragawa S, Doi K, MacMahon H, Ishida T, Yoshida H. CAD schemes for detection and characterization of interstitial disease in digital chest radiographs. Proc CAR-Computer Assisted Radiology. 1996: 380-383.
6. Yoshida H, Nishikawa RM, Giger ML, Doi K. Optimally weighted wavelet packet transform for detection of clustered microcalcifications in digital mammograms. Digital Mammography. 1996; 96: 317-322.
7. Yoshida H, Doi K, Nishikawa RM, Giger ML. Signal/background separation by wavelet packets for detection of microcalcifications in mammograms. Proc SPIE. 1996; 2825: 805-811. doi: 10.1117/12.255304
8. Yoshida H, Katsuragawa S, Amit Y, Doi K. Wavelet snake for classification of nodules and false positives in digital chest radiographs. Proc IEEE Engineering in Medicine and Biology (EMBS97). 1997; 509-512. doi: 10.1109/IEMBS.1997.757657
9. Yoshida H, Katsuragawa S. Amit Y, Doi K. Wavelet based deformable contour and its application to detection of pulmonary nodules on chest radiographs. Proc SPIE. 1997; 3169: 328-337.
10. Yoshida H, Keserci B, Doi K. Computer aided diagnosis of pulmonary nodules in chest radiographs: a wavelet based snake approach. Proc Eleventh IEEE Symposium on Computer Based Medical Systems (CBMS98). 1998: 258-263.
11. Yoshida H. Removal of normal anatomic structures in radiographs using wavelet based non-linear variational method for image matching. Proc SPIE. 1998; 3458: 174-181.
12. Yoshida H, Keserci B, Doi K. Computer aided diagnosis of pulmonary nodules in chest radiographs: distinction of nodules from false positives based on wavelet snake and artificial neural network. Computer Aided Diagnosis in Medical Imaging: Proc First International Workshop on Computer-Aided Diagnosis. Elsevier International Congress Series. 1999; 1182: 45-50.
13. Yoshida H, Anastasio A, Nagel R, Nishikawa R, Doi K. Computer aided diagnosis for detection of clustered microcalcifications in mammograms: automated optimization of performance based on genetic algorithm. Computer Aided Diagnosis in Medical Imaging: Proc First International Workshop on Computer-Aided Diagnosis. Elsevier International Congress Series. 1999: 247-252.
14. Yoshida H, Keserci B, Casalino D, Coskun A, Ozturk O, Savranlar A. Segmentation of liver tumors in ultrasound images based on scale space analysis of the continuous wavelet transform. Proc IEEE International Ultrasonics Symposium. 1999: 100-104.
15. Yoshida H. Simultaneous registration and segmentation of images in wavelet domain. Proc SPIE. 1999; 3813: 591-597.
16. Yoshida H. Multiresolution non-rigid image registration method and its application to removal of normal anatomic structures in chest radiographs. Proc IEEE International Conference on Image Processing (ICIP99). 1999; 3: 440-445.
17. Yoshida H, Doi K. Computerized detection of pulmonary nodules in chest radiographs: reduction of false positives based on bilateral symmetry of lungs. Proc SPIE. 2000; 3979: 97-102.
18. Yoshida H, Doi K. Classification of liver lesions in ultrasonic images. Proc SPIE. 2000; 3982: 252-256.
19. Yoshida H, Doi K, MacMahon H. Computerized detection of pulmonary nodules in chest radiographs: reduction of false positives based on radiologists visual analysis strategy. Proc CARS-Computer Assisted Radiology and Surgery. 2000: 809-813.
20. Yoshida H. Local contralateral subtraction based on simultaneous segmentation and registration method for computerized detection of pulmonary nodules. Proc SPIE. 2001; 4322: 426-430.
21. Yoshida H, Masutani Y, MacEneaney P, Dachman AH. Computer aided detection of polyps in CT colonography based on geometric features. Proc SPIE. 2001; 4321: 53-57.
22. Näppi J, MacEneaney P, Dachman AH, Yoshida H. Computer aided detection of polyps in CT colonography: evaluation of volumetric features in differentiating polyps from false positives. Proc CARS-Computer Assisted Radiology and Surgery. 2001; 635-640.
23. Yoshida H, Näppi J, Frimmel H, Dachman AH. Computer aided diagnosis in CT colonography: detection of polyps based on geometric and texture features. Proc SPIE. 2002; 4684: 1235-1245.
24. Näppi J, MacEneaney P, Dachman AH, Yoshida H. Effect of knowledge guided colon segmentation in automated detection of polyps in CT colonography. Proc SPIE. 2002; 4683: 222-229. doi: 10.1117/12.463586
25. Näppi J, Yoshida H. Computer aided detection of polyps in CT colonography: effect of feature guided polyp segmentation. Proc CARS-Computer Assisted Radiology and Surgery. 2002: 749-755.
26. Yoshida H. New technologies in 3D CAD for virtual colonoscopy. Proc International Conference on Diagnostic Imaging and Analysis. 2002: 29-34.
27. Dachman AH, Yoshida H. Virtual colonoscopy: past, present, and future. The Radiologic Clinics of North America. 2003; 41: 377-393.
28. Frimmel H, Näppi J, Yoshida H. Fast and robust method to compute colon centerline in CT colonography. Proc SPIE. 2003; 5031: 381-387.
29. Näppi J, Frimmel H, Yoshida H. Computer aided detection of polyps and masses for CT colonography. Proc SPIE. 2003; 5032: 860-868.
30. Näppi J, Frimmel H, Dachman AH, Yoshida H. A new high-performance CAD scheme for the detection of polyps in CT colonography. Proc SPIE. 2004; 5370: 839-348. doi: 10.1117/12.536127
31. Dachman AH, Yoshida H. CAD for CT colonography: importance and controversies. Proc CARS-Computer Assisted Radiology and Surgery. 2004; 1268: 973-977. doi: 10.1016/j.ics.2004.03.363
32. Yoshida H, Dachman AH. CAD for CT colonography: current status and future. Proc CARS-Computer Assisted Radiology and Surgery. 2004; 1268: 973-977.
33. Näppi J, Frimmel H, Okamura A, Dachman AH, Miller FH, Dalal KA, Yoshida H. Region-based supine-prone correspondence for reduction of false positives in CAD of CT colonography. Proc CARS-Computer Assisted Radiology and Surgery. 2004; 1268: 993-998. doi: 10.1016/j.ics.2004.03.248
34. Okamura A, Dachman AH, Parsad N, Näppi J, Yoshida H. Evaluation of the Effect of CAD on observers performance in detection of polyps in CT colonography. Proc CARS-Computer Assisted Radiology and Surgery. 2004; 1268: 989-992. doi: 10.1016/j.ics.2004.03.174
35. Näppi J, Yoshida H. Ranking of polyp candidates for CAD in CT colonography. Proc SPIE. 2005; 5746: 432-439. doi: 10.1117/12.596432
36. Cai W, Dachille F, Harris GJ, Yoshida H. Vesselness propagation-a fast interactive vessel structure segmentation method. Proc SPIE. 2006; 6144: 614447-1-8.
37. Cai W, Näppi J, Zalis ME, Harris GJ, Yoshida H. Digital bowel cleansing for computer-aided detection of polyps in fecal-tagging CT colonography. Proc SPIE. 2006; 6144: 614422-1-9.
38. Näppi J, Frimmel H, Yoshida H. Centerline-based colon segmentation for CAD of CT colonography. Proc SPIE. 2006; 6144: 61445H-1-8.
39. Cai W, Yoshida H, Harris GJ. Dynamic-thresholding level set: a novel computer-aided volumetry method for liver tumors in hepatic CT images. Proc SPIE. 2007; 65142W-1-8.
40. Näppi J, Yoshida H, Zalis M, Cai W, Lefere P. Pseudo-enhancement correction for computer-aided detection in fecal-tagging CT colonography. Proc SPIE. 2007; 6514: 65140A-1 -1-8.
41. Nagata K, Näppi J, Cai W, Yoshida H. Minimum-invasive early diagnosis of colorectal cancer with CT colonography: techniques and clinical value. Expert Opin Med Diagn. 2008; 2: 1233-1246. doi: 10.1517/17530059.2.11.1233
42. Cai W, Zalis M, Yoshida H. Mosaic decomposition method for detection and removal of inhomogeneously tagged regions in electronic cleansing for CT colonography. Proc SPIE. 2008; 6915: 69150D-1-8.
43. Cai W, Zalis ME, Yoshida H. Reduction of electronic-cleansing artifacts in cathartic and non-cathartic fecal-tagging CT colonography. Proc MICCAI 2008 Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy. 2008: 70-77.
44. Näppi J, Yoshida H. Automated scheme for preparation-independent detection of colorectal lesions in CT colonography. Proc MICCAI 2008 Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy. 2008: 127-135.
45. Seghouane A-K, Näppi J, Yoshida H. Feature selection with BIC and PCA for polyp detection in CT colonography. Proc MICCAI 2008 Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy. 2008: 64-69.
46. Yoshida H, Näppi J. CAD in CT colonography: past, present, and future. Proc MICCAI 2008 Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy. 2008: 19-21.
47. Cai W, Yoshida H, Zalis M. Electronic fecal tagging: reduction of inhomogeneous tagging for detection of polyps in non-cathartic CT colonography. Proc SPIE. 2009; 6915: 69150D-1-8.
48. Näppi J, Cai W, Yoshida H. Computer-aided detection of colorectal lesions for cathartic-free CT colonography. Proc Sixth IEEE International Symposium on Biomedical Imaging (ISBI09). 2009: 911-914.
49. Yoshida H, Näppi J, Cai W. Computer-aided detection of polyps in CT colonography: performance evaluation in comparison with human readers based on large multicenter clinical trial cases. Proc Sixth IEEE International Symposium on Biomedical Imaging (ISBI09). 2009: 919-922.
50. Singh AK, Yoshida H, Sahani DV. Advanced postprocessing and the emerging role of computer-aided detection. Radiologic Clinics of North America. 2009; 47: 59-77. doi: 10.1016/j.rcl.2008.11.004
51. Cai W, Liu, B, Yoshida H. Dual-energy electronic cleansing for non-cathartic CT Colonography: a phantom study. Proc SPIE. 2010; 7624: 76240C-1-8.
52. Sainani NI, Näppi J, Sahani DV, Yoshida H. Computer-aided detection of small bowel strictures in CT enterography. Proc SPIE. 2011; 7963: 79632J-1-6.
53. Näppi J, Regge D, Yoshida H. Probabilistic method for context-sensitive detection of polyps in CT colonography. Proc SPIE. 2011; 7963: 79631D-1-6.
54. Cai W, Yoshida H. Electronic cleansing in CT colonography: past, present, and future. Virtual Colonoscopy and Abdominal Imaging 2010, Lecture Notes in Computer Science. 2011; 6668: 1-8. doi: 10.1007/978-3-642-25719-3_1
55. Näppi J, Lee J-G, Fletcher JG, Yoshida H. Computer-assisted diagnosis for quantitative image-based analysis of Crohns disease in CT enterography. Virtual Colonoscopy and Abdominal Imaging 2010, Lecture Notes in Computer Science. 2011; 6668: 84-90.
56. Lee J-G, Cai W, Singh A, Yoshida H. Estimation of necrosis volumes in focal liver lesions based on multi-phase hepatic CT images. Virtual Colonoscopy and Abdominal Imaging 2010, Lecture Notes in Computer Science. 2011; 6668: 60-67.
57. Sainani N, Näppi J, Sahani DV, Yoshida H. Computer-aided detection of small bowel strictures for emergency radiology in CT enterography. Virtual Colonoscopy and Abdominal Imaging 2010, Lecture Notes in Computer Science. 2011; 6668: 91-97. doi: 10.1007/978-3-642-25719-3_13
58. Cai W, Lee J-G, Kim S-H, Yoshida H. Dual-energy electronic cleansing for artifact-free visualization of the colon in fecal-tagging CT colonography. Abdominal Imaging 2011, Lecture Notes in Computer Science. 2012; 7029: 8-17. doi: 10.1007/978-3-642-28557-8_2
59. Näppi J, Regge D, Yoshida H. Comparative performance of random forest and support vector machine classifiers for detection of colorectal lesions in CT colonography. Abdominal Imaging 2011, Lecture Notes in Computer Science. 2012; 7029: 27-34. doi: 10.1007/978-3-642-28557-8_4
60. Näppi J, Regge D, Yoshida H. Ensemble detection of colorectal lesions for CT colonography. Abdominal Imaging 2011, Lecture Notes in Computer Science. 2012; 7029: 60-67. doi: 10.1007/978-3-642-28557-8_8
61. Näppi J, Gryspeerdt S, Lefere P, Zalis M, Yoshida H. Automated detection of colorectal lesions in non-cathartic CT colonography. Abdominal Imaging 2011, Lecture Notes in Computer Science. 2012; 7029: 68-75.
62. Näppi J, Sahani DV, Fletcher JG, Yoshida H. Automated detection and diagnosis of Crohns disease in CT enterography. Abdominal Imaging 2011, Lecture Notes in Computer Science. 2012; 7029: 84-90.
63. Näppi J, Kim S-H, Yoshida H. Automated detection of colorectal lesions with dual-energy CT colonography. Proc SPIE. 2012; 7963: 79632J-1-6.
64. Cai W, Kim S-H, Lee J-G, Yoshida H. Virtual colon tagging for electronic cleansing in dual-energy fecal-tagging CT colonography. Proc IEEE Eng Med Biol Soc. 2012; 2012: 3736-3739.
65. Näppi J, Kim S-H, Yoshida H. Volumetric detection of colorectal lesions for noncathartic dual-energy computed tomographic colonography. Proc IEEE Eng Med Biol Soc. 2012; 2012: 3740-3743.
66. Yoshida H, Wu, Y, Cai W. Scalable, high-performance 3D image computing platform: system architecture and application to virtual colonoscopy. Proc IEEE Eng Med Biol Soc. 2012; 2012: 3994-3997.
67. Näppi J, Kim S-H, Yoshida H. Adaptive volumetric detection of lesions for minimal-preparation dual-energy CT colonography. Abdominal Imaging 2012, Lecture Notes in Computer Science. 2012; 7601: 30-39.
68. Näppi J, Imuta M, Yamashita Y, Yoshida H. Computer-aided detection for ultra-low-dose CT colonography. Abdominal Imaging 2012, Lecture Notes in Computer Science. 2012; 7601: 40-48.
69. Näppi J, Rockey D, Regge D, Yoshida H. Application of CT acquisition parameters as features in computer-aided detection for CT colonography. Abdominal Imaging 2012, Lecture Notes in Computer Science. 2012; 7601: 69-77. doi:10.1007/978-3-642-33612-6_8
70. Lee S-H, Näppi J, Yoshida H. Comparative performance of state-of-the-art classifiers in computer-aided detection for CT colonography. Abdominal Imaging 2012, Lecture Notes in Computer Science. 2012; 7601: 78-87. doi: 10.1007/978-3-642-33612-6_9
71. Cai W, Lee J-G, Zhang D, Piel C, Yoshida H. Piecewise structural diffusion defined on shape index for noise reduction in dual-energy CT images. Abdominal Imaging 2012, Lecture Notes in Computer Science. 2012; 7601: 88-96.
72. Lee S-H, Cai W, Yoshida H. Tracer kinetic modeling by Morales-Smith hypothesis in hepatic perfusion CT. Abdominal Imaging 2012, Lecture Notes in Computer Science. 2012; 7601: 292-302. doi: 10.1007/978-3-642-33612-6_31
73. Näppi J, Kim S-H, Yoshida H. Volumetric detection of flat lesions for minimal-preparation dual-energy CT colonography. Proc SPIE. 2013; 8670: 86702E-1-6.
74. Cai W, Zhang D, Lee J-G, Yoshida H. Low-dose dual-energy electronic cleansing for fecal-tagging CT colonography. Proc SPIE. 2013; 8670: 86700W-1-9. doi: 10.1117/12.2008127
75. Näppi JJ, Do S, Yoshida H. Computer-aided detection of colorectal lesions with super-resolution CT colonography: Pilot evaluation. Abdominal Imaging 2013, Lecture Notes in Computer Science. 2013; 8198: 73-80. doi: 10.1007/978-3-642-41083-3_9
76. Do S, JJ. Näppi, Yoshida H, Iterative reconstruction for ultra-low-dose laxative-free CT Colonography. Abdominal Imaging 2013, Lecture Notes in Computer Science. 2013; 8198: 99-106.
77. Ryu Y, Näppi JJ, Phan M, Yoshida H. Computer-aided detection of non-polypoid flat lesions in CT colonography: Observer performance study. Abdominal Imaging 2013, Lecture Notes in Computer Science. 2013; 8198: 81-88. doi: 10.1007/978-3-642-41083-3_10
78. Lee SH, Ryu Y, Hayano K, Yoshida H. Continuous-time flow-limited modeling by convolution area property and differentiation product rule in 4-phase liver dynamic contrast-enhanced CT. Abdominal Imaging 2013, Lecture Notes in Computer Science. 2013; 8198; 259-269. doi: 10.1007/978-3-642-41083-3_29
79. Lee SH, Hayano K, Sahani D, Yoshida H. Use of tracer kinetic model-driven biomarkers for monitoring antiangiogenic therapy of hepatocellular carcinoma in first-pass perfusion CT. Abdominal Imaging 2013, Lecture Notes in Computer Science. 2013; 8198: 270-279. doi: 10.1007/978-3-642-41083-3_30
80. Yoshida H, Wu Y, Cai W. Analysis of scalability of high-performance 3D image processing platform for virtual colonoscopy. Proc Soc Photo Opt Instrum Eng. 2014; 9039: 90390U. doi: 10.1117/12.2043869
81. Näppi J, Ryu Y, Yoshida H. Progressive region-based colon extraction for computer-aided detection and quantitative imaging in cathartic and non-cathartic CT colonography. Proc Soc Photo Opt Instrum Eng. 2014; 9035: 90352X. doi: 10.1117/12.2043890
82. Lee SH, Hayano K, Sahani D, Zhu A, Yoshida H. Parameter comparison between fast-water-exchange-limit-constrained standard and water-exchange-modified dual-input tracer kinetic models for DCE-MRI in advanced hepatocellular carcinoma. ABDI 2014, Lecture Notes in Computer Science. 2014; 8676: 33-47. doi: 10.1007/978-3-319-13692-9_4
83. Lee SH, Hayano K, Sahani D, Zhu A, Yoshida H. Kinetic Textural Biomarker for Predicting Survival of Patients with Advanced Hepatocellular Carcinoma after Antiangiogentic Therapy by Use of Baseline First-Pass Perfusion CT. ABDI 2014, Lecture Notes in Computer Science. 2014; 8676: 48-61. doi: 10.1007/978-3-319-13692-9_5
84. Lee SH, Yasuji Ryu, Hayano K, Yoshida H. Feasibility of single-input tracer kinetic modeling with continuous-time formalism in liver 4-phase dynamic contrast-enhanced CT. ABDI. 2014, Lecture Notes in Computer Science. 2014; 8676: 62-73. doi: 10.1007/978-3-319-13692-9_6
85. Näppi J, Tachibana R, Regge D, Yoshida H. Information-preserving pseudo-enhancement correction for non-cathartic low-dose dual-energy CT colonography. Abdominal Imaging. 2014, Lecture Notes in Computer Science. 2014; 8676: 159-168.
86. Tachibana R, Näppi J, Yoshida H. Application of pseudo-enhancement correction to virtual monochromatic CT colonography. ABDI 2014, Lecture Notes in Computer Science. 2014; 8676: 169-178.
87. Näppi J, Regge D, Yoshida H. Context-specific method for detection of soft-tissue lesions in non-cathartic low-dose dual-energy CT colonography. Proc Soc Photo Opt Instrum Eng. 2015; 9414: 94142Y.
88. Tachibana R, Näppi J, Kim SH, Yoshida H. Electronic cleansing for dual-energy CT colonography based on material decomposition and virtual monochromatic imaging. Proc Soc Photo Opt Instrum Eng. 2015; 9414: 94140Q. doi: 10.1117/12.2082375
89. Nasirudin RA, Tachibana R, Näppi JJ, et al. A comparison of material decomposition techniques for dual-energy CT colonography. Proc Soc Photo Opt Instrum Eng. 2015; 9412: 94122E-1-6. doi: 10.1117/12.2081982

REVIEWS, CHAPTERS, MONOGRAPHS AND EDITORIALS

1. Yoshida H. Explicit derivation of Gauss Bonnet combination from string theories. University of Tokyo, Elementary Particle Physics Laboratory (EPPL) Technical Report. 1986: UT 481.
2. Liang JZ, Higgins WE, Summers RM, Yoshida H. Introduction to the special section on virtual endoscopy. Editorial. IEEE Transactions on Medical Imaging. 2004; 23: 1333-1334.
3. Yoshida H, Svoboda AC, and Orton CG. Within the next five years CT colonography will make conventional colonoscopy obsolete for colon cancer screening. Point/Counterpoint. Medical Physics. 2006; 33: 2679-2682.
4. Yoshida H. Wavelet transform. In: Uchida S, Odera Y, Fujita H, editors, Digital Diagnostic Radiology. Ohmu-Sya. 1998; 19-30.
5. Yoshida H, Katsuragawa S, Amit Y, Doi K. Wavelet-based deformable contour and its application to detection of pulmonary nodules on chest radiographs. In: Ritter GX, ed. Selected SPIE Papers on CD-ROM. Mathematical Imaging and Vision. The International Society for Optical Engineering. 1999; 8.
6. Yoshida H. Neural network for classification of focal liver lesions in ultrasound images. In: Jain LC De Wilde P, eds. Practical Applications of Soft Computing Techniques. Kluwer Academic Publishers. 2001; 355-378.
7. Yoshida H. Wavelets for computer-aided diagnosis in medical imaging. In: Petrosian AA, Meyer FG, eds. Wavelets in Signal and Image Analysis. Kluwer Academic Publishers; 2001; 418-452.
8. Summers RM, Yoshida H. Future directions of CT colonography: computer-aided diagnosis. In Dachman AH editor. Atlas of Virtual Colonoscopy. Springer; 2003; 55-62.
9. Dachman AH, Glick S, Yoshida H. Colon cancer screening: the potential role of virtual colonoscopy. In: DeVita VT, Hellman S, Rosenberg SA, eds. Progress in Oncology. Jones and Bartlett, Massachusetts. 2003; 298-313.
10. Summers RM, Yoshida H. Future directions: computer-aided diagnosis. In: Dachman AH, ed. Fundamentals of Virtual Colonoscopy. Springer; 2005; 79-89.
11. Dachman AH, Yoshida H. Virtual endoscopic imaging. In: Weinstein W, Hawkey CJ, Bosch J, eds. Gastroenterology and hepatology: the modern clinicians guide. Elsevier Science, London, UK; 2005. 129: 955-962.
12. Yoshida H. Chapter 11: The future: computer-aided detection. In: Lefere P, Gryspeerdt S, eds. Virtual colonoscopy: a practical guide. Springer. 2005; 137-151.
13. Yoshida H. Computer-aided diagnosis for virtual colonoscopy. In: Zharkova V, Jain L, eds. Artificial intelligence in recognition and classification of astrophysical and medical images. Springer. 2007; 302-338.
14. Yoshida H, Dachman AH. Computer Aided Diagnosis: Clinical Applications in CT Colonography. In: Neri E, Caramella D, Bartolozzi C, editors. Image Processing in Radiology: Current Applications. Springer. 2007; 375-392.
15. Singh AK, Harris GJ, Cai W, Sahani D.V, Yoshida H. Chapter 24: Principles of 3D post-processing, Abdominal Imaging. In: Sahani D, Samir A, eds. Elsevier: Saunders. 2010; 159-170.
16. Singh AK, Harris GJ, Sahani DV, Cai W, Yoshida H. Chapter 25: Advanced applications of post-processing, Abdominal Imaging. In: Sahani D, Samir A, eds. Elsevier: Saunders; 2010; 171-182.
17. Singh AK, Harris GJ, Yoshida H, Sahani DV. Chapter 60: CT of the liver, Abdominal Imaging. In: Sahani D, Samir A, eds. Elsevier: Saunders; 2010; 517-528.
18. Yoshida H, Cadi M. CAD, Coloscopie virtuelle. In: Cadi M, ed. Lavoisier. 2010; 106-128.
19. Yoshida H. Chapter 14: The future: computer-aided detection. In: Lefere P, Gryspeerdt S, eds. Virtual colonoscopy: a practical guide (2nd revised edition). Springer; 2010; 175-189.

BOOKS/TEXTBOOKS FOR THE MEDICAL OR SCIENTIFIC COMMUNITY

1. Yoshida H, Takahara T. Windows magic, Koei Publishing Company; 1992.
2. Yoshida H, Takahara T. authors. The best guide to NeXT computers. Koei Publishing Company; 1992.
3. Yoshida H, editor. Introduction to the BASIC programming language. Fuji Software Inc.; 1992.
4. Yoshida H, editor. Essential LAN terminology 100. Koei Publishing Company; 1993.
5. Yoshida H, editor. The best guide to the World Wide Web. Koei Publishing Company; 1996.
6. Yoshida H, editor. Essential network terminology 100. Koei Publishing Company; 1997.
7. Yoshida H, editor. The internet dictionary, Koei Publishing Company; 1997.
8. Yoshida H, Jain A Ichalkaranje A, Jain LC. Advanced Computational Intelligence Paradigms in Healthcare . Springer; 2007.
9. Vaidya S, Jain LC, Yoshida H. Advanced Computational Intelligence Paradigms in Healthcare. Springer; 2007.
10. Toriwaki J, Yoshida H. Fundamentals of Three-dimensional Digital Image Processing. Springer; 2009.
11. Yoshida H, Cai W. Virtual Colonoscopy and Abdominal Imaging: Computational Challenges and Clinical Opportunities (Second International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 2010, Revised Selected Papers), Lecture Notes in Computer Science. Springer. 2011; 6668: 141.
12. Yoshida H, Sakas G, Linguraru M. Abdominal Imaging: Computational and Clinical Applications (Third International Workshop, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 2011, Revised Selected Papers), Lecture Notes in Computer Science. Springer. 2012; 7029: 274.
13. Yoshida H, Hawkes D, Vannier, M. Abdominal Imaging: Computational and Clinical Applications (Fourth International Workshop, Held in Conjunction with MICCAI 2012, Nice, France, October 2012, Proceedings), Lecture Notes in Computer Science. 2012; 7601: 318.
14. Yoshida H, Warfield S, Vannier M. Abdominal Imaging: Computational and Clinical Applications (5th International Workshop, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September, 2013, Proceedings), Lecture Notes in Computer Science. 2013; 8198: 300.
15. Yoshida H, Näppi JJ, Saini S. Abdominal Imaging: Computational and Clinical Applications (6th International Workshop, ABDI 2014, Held in Conjunction with MICCAI 2014, Cambridge, MA, USA, September 14, 2014), Lecture Notes in Computer Science. 8676: 296.

LETTERS TO THE EDITOR

1. Evancho AM, Yoshida H, Dachman A. Computer aided diagnosis: blessing or curse? Radiology. 2002; 225: 606-607.
2. Cai W, Lee JG, Yoshida H, Kim SH. Respond to Dual-energy CT for diagnostic CT colonography. Radiographics. 2014; 34: 848.