Diagnostic decision-making in pulmonary medical imaging has been improved by computer-aided diagnosis (CAD) systems, serving as second readers to detect suspicious nodules for dia...
William Horsthemke, Ekarin Varutbangkul, Daniela S...
We use the data collected by the Lung Image Database Consortium (LIDC) for modeling the radiologists’ nodule interpretations based on image content of the nodule by using decisi...
Ekarin Varutbangkul, Vesna Mitrovic, Daniela Stan ...
We present LungCAD, a computer aided diagnosis (CAD) system that employs a classification algorithm for detecting solid pulmonary nodules from CT thorax studies. We briefly descri...
R. Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salgan...
There is considerable research in the field of content-based medical image retrieval; however, few of the current systems investigate the relationship between the radiologists’...
Robert Kim, Grace Dasovich, Runa Bhaumik, Richard ...
A mathematical programming formulation is proposed to eliminate irrelevant and redundant features for collaborative computer aided diagnosis which requires to detect multiple clin...