CAD Poster

095 Pulmonary nodule classification with 3D features of texture and margin sharpness
P.M. Azevedo-Marques, J. Ferreira Jr, Univ. of Sao Paulo, Ribeirao Preto, M. C. Oliveira, UFAL, Maceio (BR)

096 Proposal for a novel CAD development technique using artificially created case images
K. Abe, H. Takeo, Kanagawa Institute of Technology, Y. Kuroki, Kameda Kyobashi Clinic, Tokyo, Y. Nagai, Higashisaitama National Hospital, Saitama (J)

097 Usefulness of a z-score-based analysis of the temporal horn volume of the lateral ventricle for detection of early Alzheimer’s disease on CT images
N. Takahashi, T. Kinoshita, T. Ohmura, Y. Lee, E. Matsuyama, H. Toyoshima, Research Institute for Brain and Blood Vessels, Akita (J)

098 Information gain analysis of mammographic features of breast masses using machine learning
R. Raju, Univ. of Illinois at Chicago (USA)

099 Automatic diagnosis module for in-vivo optical biopsy
L. Gruionu, G. Gruionu, Univ. of Craiova, D. Stefanescu, C. Streba, T. Cartana, A. Saftoiu, Univ. of Medicine and Pharmacy Craiova (RO)

100 A method for highlighting lung tuberculosis lesions in CT images using superpixel approach
V. Liauchuk, V. Kovalev, United Inst. of Informatics, A. Astrauko, Scientific and Practical Center for Pulmonology and Tuberculosis, Minsk (BY), A. Rosenthal, A. Gabrielian, National Inst. of Allergy and Infectional Diseases, Bethesda, MD (USA)

101 Value of nested contours analysis algorithm in mammographic image processing
I. Egoshin, D. Pasynkov, Mari State Univ., Yoshkar-Ola, A. Kolchev, Kazan Federal Univ., I. Kliouchkin, Kazan State Medical Univ. (RUS)