EC882 Computer Aided Diagnosis
Course Name:
EC882 Computer Aided Diagnosis
Programme:
M.Tech(SPML)
Category:
Elective (Ele)
Credits (L-T-P):
(3-0-2) 4
Content:
Introduction to human anatomy, diseases, and diagnostic imaging; History of Computer Aided Diagnosis systems; Morphological, texture, shape descriptors, and radiomics; Imaging biomarkers; Computational methods for risk assessment, disease detection and staging, disease prognosis, and outcome prediction; Segmentation methods; Image registration methods; Classification methods; Evaluation methods: sensitivity, specificity, accuracy, receiver operating characteristic (ROC) analysis; Recent advances in Computer Aided Diagnosis.
References:
Sun, Ellen X., Junzi Shi, and Jacob C. Mandell, eds. Core radiology: A visual approach to diagnostic imaging.
Cambridge University Press, 2021
De Azevedo-Marques, Paulo Mazzoncini, Arianna Mencattini, Marcello Salmeri, and Rangaraj M. Rangayyan, eds.
Medical Image Analysis and Informatics: Computer-Aided Diagnosis and Therapy. CRC Press, 2017.
Li, Qiang, and Robert M. Nishikawa, eds. Computer-aided detection and diagnosis in medical imaging. Taylor &
Francis, 2015.
Department:
Electronics and Communication Engineering(ECE)