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- W4285297430 abstract "Knee ligament injury is a common medical dilemma affecting the sportsman and common people during their prolific years of career. It is possible to visualize soft tissue elements, bone and cartilage of the knee joint using Magnetic Resonance Imaging (MRI) leads it to the most popular method for detection and diagnosis for knee ligament injury or intra-articular structure injury, gives best visualization result. Analysis of MRI images, manually is time consuming, subjective and unpredictable. Ligament injury can be detected automatically using image segmentation and various techniques like machine learning; deep learning where layers will be learned features automatically and are appropriately model the complex structure and their interpretations. In this paper, techniques used for the detection of knee ligament injury partial or complete are covered." @default.
- W4285297430 created "2022-07-14" @default.
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- W4285297430 date "2022-01-01" @default.
- W4285297430 modified "2023-09-26" @default.
- W4285297430 title "Role of Deep Learning and Machine Learning in Automatic Knee Ligament Injury Detection" @default.
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- W4285297430 doi "https://doi.org/10.1007/978-981-16-7985-8_21" @default.
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