Bone Image Analysis For Early Detection of Osteoporosis

Numerous studies believe that bone mineral density (BMD) is the only technique that fundamentally reveals bone strength, despite the fact that the latter provides important information regarding the risk of osteoporotic fracture. Analyzing macro- and micro-structural characteristics quantitatively may improve beyond simply estimating bone density. Bone structural information can be obtained using non-interfering, non-carnage procedures. According to many research, bone mineral densitometry (BMD), which also provides important information on osteoporosis, primarily measures bone strength. Numerous works in the field of photo-domain computer vision have introduced efficient strategies that benefit from different viewpoints on the same instance in other domains such as self-supervised and semi-supervised learning. In order to tackle these problems we are using a simple yet efficient method termed as multi-view ct network or mvctnet along with multimodal data fusing technique called Early Fusion. Utilizing cutting-edge methods and technologies will improve image analysis in multi-view CT scanning for osteoporosis detection, increasing the precision and effectiveness of osteoporosis detection.