State-of-the-Art of Computer-Aided Detection/Diagnosis (CAD)

This paper summarizes the presentations given in the special ICMB2010 session on state-of-the-art of computer-aided detection/diagnosis (CAD). The topics are concerned with the latest development of technologies and applications in CAD, which include brain MR images, fundus photographs, dynamic chest radiography, chest CT images, whole breast ultrasonography, CT colonography and torso FDG-PET scans.

[1]  Morson Bc,et al.  The Polyp-cancer Sequence in the Large Bowel , 1974 .

[2]  Hiroshi Fujita,et al.  Development of a fully automatic scheme for detection of masses in whole breast ultrasound images. , 2007, Medical physics.

[3]  David Zhang,et al.  A Modified Matched Filter With Double-Sided Thresholding for Screening Proliferative Diabetic Retinopathy , 2009, IEEE Transactions on Information Technology in Biomedicine.

[4]  Jeanne A. Cullinan IWDM 2000: 5th International Workshop on Digital Mammography , 2002 .

[5]  K. Doi,et al.  Computerized detection of intracranial aneurysms for three-dimensional MR angiography: feature extraction of small protrusions based on a shape-based difference image technique. , 2006, Medical physics.

[6]  Hiroshi Honda,et al.  Automated method for identification of patients with Alzheimer's disease based on three-dimensional MR images. , 2008, Academic radiology.

[7]  Xiangrong Zhou,et al.  Automated scoring system of standard uptake value for torso FDG-PET images , 2008, SPIE Medical Imaging.

[8]  Daisuke Yamamoto,et al.  Computer-aided detection of multiple sclerosis lesions in brain magnetic resonance images: False positive reduction scheme consisted of rule-based, level set method, and support vector machine , 2010, Comput. Medical Imaging Graph..

[9]  Yasuo Yamashita,et al.  Computer-aided evaluation method of white matter hyperintensities related to subcortical vascular dementia based on magnetic resonance imaging , 2010, Comput. Medical Imaging Graph..

[10]  Daisuke Yamamoto,et al.  Computer-Aided Diagnosis Systems for Brain Diseases in Magnetic Resonance Images , 2009, Algorithms.

[11]  Hiroshi Fujita,et al.  Detection, Characterization, and Visualization of Breast Cancer Using 3D Ultrasound Images , 2006 .

[12]  Hiroshi Fujita,et al.  Classification of Benign and Malignant Masses in Ultrasound Breast Image Based on Geometric and Echo Features , 2008, Digital Mammography / IWDM.

[13]  Rangaraj M. Rangayyan,et al.  Recent Advances in Breast Imaging, Mammography, and Computer-Aided Diagnosis of Breast Cancer , 2006 .

[14]  Stuart A. Taylor,et al.  CT colonography: computer-aided detection of morphologically flat T1 colonic carcinoma , 2008, European Radiology.

[15]  Yasuaki Arai,et al.  The Challenge: Detection of Early-Stage Superficial Colorectal Lesions , 2010 .

[16]  A.D. Hoover,et al.  Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response , 2000, IEEE Transactions on Medical Imaging.

[17]  H. Fujita,et al.  Computer-aided diagnosis scheme for detection of lacunar infarcts on MR images. , 2007, Academic Radiology.

[18]  A. M. Youssef,et al.  Automated polyp detection at CT colonography: feasibility assessment in a human population. , 2001, Radiology.

[19]  Hiroshi Fujita,et al.  Semi-automatic ultrasonic full-breast scanner and computer-assisted detection system for breast cancer mass screening , 2007, SPIE Medical Imaging.