首页|Recent Research from Bangalore University Highlight Findings in Pattern Recognit ion and Artificial Intelligence (Efficient Hand Bone Segmentation for Medical Ap plications Using Refined Deeplab Model)
Recent Research from Bangalore University Highlight Findings in Pattern Recognit ion and Artificial Intelligence (Efficient Hand Bone Segmentation for Medical Ap plications Using Refined Deeplab Model)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing - Pattern Recognition and Artificial Intelligence have been published. Accor ding to news reporting originating from Bengaluru, India, by NewsRx corresponden ts, research stated, “In the medical field, analyzing various bone structures is crucial due to the rigid nature of bones. X-ray imaging plays an essential role in medical procedures, including bone age evaluation, fracture detection, and i mplant creation.” Our news editors obtained a quote from the research from Bangalore University, “ However, operator involvement can introduce biases and increase processing time. Automating the process could reduce processing time and enhance diagnostic accu racy by minimizing biases and operator involvement. This paper introduces the Re fined DeepLab model, a lightweight encoder-decoder-based approach for multiclass segmentation of hand bones. The primary objective is to assist physicians in ta sks such as bone age analysis, fracture detection, hand movement analysis, and i mplant design. The research objectives are organized into three phases, with thi s work focusing on the first phase of our objectives, which is delineating bones from tissues, studying the bone structure, and multiclass segmentation of hand bones. The model utilizes DenseNet121 as its feature extractor and Sigmoid-weigh ted Linear Unit (SiLU) as its activation function. Experimental findings demonst rate promising performance in hand bone multiclass segmentation, with a Mean Int ersection over Union (mIoU) of 85.02% and a Dice score of 92.2% .”
BengaluruIndiaAsiaPattern Recognit ion and Artificial IntelligenceMachine LearningBone ResearchHealth and Med icineBangalore University
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