Paper
31 January 2020 Enhanced single shot detector with image sharpening for detection of knee joint
Author Affiliations +
Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114330C (2020) https://doi.org/10.1117/12.2557509
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands
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.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Trupti Chavan, Guda Ramachandra Kaladhara Sarma, and Kameshwar Rao "Enhanced single shot detector with image sharpening for detection of knee joint", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114330C (31 January 2020); https://doi.org/10.1117/12.2557509
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KEYWORDS
Image enhancement

Medical imaging

X-ray imaging

X-rays

Image segmentation

Magnetic resonance imaging

Sensors

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