By Jinshan Tang, Sos S. Agaian
Actual imaging of cancerous tissue is a serious step within the struggle to decrease melanoma mortality premiums, and computer-aided detection and analysis (CAD) applied sciences play a key function. during the last 3 many years, the sphere of diagnostic melanoma imaging has witnessed a amazing evolution that has affected nearly each point of analysis and scientific administration of melanoma. This ebook discusses fresh high-quality learn in key applied sciences utilized in CAD platforms; the eleven chapters disguise varieties of cancers (including epidermis, breast, prostate, and colon melanoma) and diverse clinical fields (such as biomedicine, imaging, picture processing, trend acceptance, and process research) to extra the foremost ambitions of present melanoma imaging: offer extra trustworthy ailment characterization in the course of the synthesis of anatomic, useful, and molecular imaging info; refine and optimize imaging services in oncology; identify new imaging modalities and findings, and detect the capability use of those innovations; locate extra individualized overview of tumor biology, customized remedies, and reaction to therapy; enhance image-processing-based melanoma regulate structures; and discover imaging functions and methods to streamline melanoma drug development. Read more...
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Additional resources for Computer-aided cancer detection and diagnosis : recent advances
Yao and R. M. Summers, “Adaptive deformable model for colonic polyp segmentation and measurement on CT colonography,” Med. Phys. 34(5), 1655–1664 (2007). 43. M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int. J. Comput. Vision 1(4), 321–331 (1988). 44. J. J. Koenderink and A. J. van Doorn, “Surface shape and curvature scales,” Image and Vision Computing 10(8), 557–565 (1992). 45. A. Huang, D. Roy, and R. M. Summers. , Baltimore, MD (2005). 46. I. N. Bankman, T. S. Spisz, and S.
Medical Image Processing and Analysis, M. Sonka and J. M. ch10]. Jianhua Yao, PhD, is an associate scientist and manager in the Radiology and Imaging Sciences Department at the National Institutes of Health. D. in Computer Science from Tianjin University (China), Tsinghua University (China), and Johns Hopkins University, respectively. His research interests include clinical image processing, deformable models, nonrigid registration, computer-aided diagnosis, and CT colonography. Chapter 2 Preprocessing Tools for Computer-Aided Cancer Imaging Systems Artyom M.
Summers. “Radon transform based polyp segmentation method for CT colonography computer aided diagnosis,” Radiology 225(P), 257 (2002). 41. J. J. Dijkers et al. “Segmentation and Size Measurement of Polyps in CT Colonography,” in MICCAI, Springer-Verlag, Berlin (2005). 42. J. Yao and R. M. Summers, “Adaptive deformable model for colonic polyp segmentation and measurement on CT colonography,” Med. Phys. 34(5), 1655–1664 (2007). 43. M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” Int.
Computer-aided cancer detection and diagnosis : recent advances by Jinshan Tang, Sos S. Agaian