Ender Konukoglu

TL;DR: In this paper, the longitudinal performance of fully automated cartilage segmentation in knees with radiographic osteoarthritis (ROA) was evaluated by evaluating the sensitivity to change in progressor knees from the Foundation National Institutes of Health OA Biomarkers Consortium, and whether differences in progression rates between predefined cohorts can be detected by the fully automated approach.

TL;DR: In this paper, a convolutional neural network (CNN) was used to decide on the necessity of dynamic contrast-enhanced sequences (DCE) in prostate MRI, which achieved a sensitivity of 94.4% and specificity of 68.5%.

TL;DR: Wang et al. as discussed by the authors proposed a quality-aware memory network for interactive segmentation of 3D medical images, where an interaction network is firstly employed to obtain an initial 2D segmentation, and then the network propagates the initial segmentation estimation bidirectionally over the entire volume.

TL;DR: This study established normative values of TA features on CT images of the spine and showed age-, gender-, and regional-specific differences in individuals with normal BMD as defined by DXA.

TL;DR: It is shown that the local Gaussian approximator can be applied to several auto-encoding models to perform image restoration and unsupervised lesion detection and achieves state-of-the-art results.