The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date; (b) identify common and unique …

Deep learning is the state-of-the-art machine learning approach. The success of deep learning
in many pattern recognition applications has brought excitement and high expectations …

Computer‐aided diagnosis (CAD) has been a major field of research for the past few decades.
CAD uses machine learning methods to analyze imaging and/or nonimaging patient data …

We are developing a computer‐aided diagnosis (CAD) system for lung nodule detection on
thoracic helical computed tomography (CT) images. In the first stage of this CAD system, …

Digital tomosynthesis mammography (DTM) is a promising new modality for breast cancer
detection. In DTM, projection‐view images are acquired at a limited number of angles over a …

… To address these challenges, Hadjiiski et al. developed preliminary bladder segmentation
methods for CTU using active contour with 15 patients and level sets with 70 patients. …

We are developing a computer‐aided diagnosis (CAD) system to classify malignant and
benign lung nodules found on CT scans. A fully automated system was designed to segment …

… , and D are the average gray values inside four boxes of size 8 × 8 pixels at the left, right,
upper, and bottom periphery of the ROI, weighted inversely by the perpendicular distance of d l …

… The likelihood L describes how close the real peak is to the triangle represented by the …
right side of PM by the features E, EL , ER and L, and the relative position of the two peaks. If the …

We are developing new computer vision techniques for characterization of breast masses on
mammograms. We had previously developed a characterization method based on texture …