Enhanced single shot detector with image sharpening for detection of knee joint

Abstract

The abrupt movements, accidents, aging and obesity cause different kinds of knee dysfunctions. Therefore, the automatic detection of knee can serve a great purpose in planning related surgeries. The biggest challenge in medical imaging is to get the large number of images along with annotations which are needed for the successful working of convolutional neural networks (CNNs). Sometimes, the contrast of X-ray images is also very poor; the edges of targets are not clear in some radiographs and it becomes difficult for humans to locate the desired area in the images. This work introduces enhanced single shot detection (SSD) to tackle the automatic knee detection and localization problem. Image sharpening is used for pre-processing to handle the poor contrast issue. The dataset used to verify the proposed method is collected from the openly available online sources and the proposed approach has achieved 96.76% mAP.