NAMSTCD: A Novel Augmented Model for Spinal Cord Segmentation and Tumor Classification Using Deep Nets.

Spinal cord segmentation is the process of identifying and delineating the boundaries of the spinal cord in medical images such as magnetic resonance imaging (MRI) or computed tomography (CT) scans. This process is important for many medical applications, including the diagnosis, treatment planning, and monitoring of spinal cord injuries and diseases. The segmentation process involves using image processing techniques to identify the spinal cord in the medical image and differentiate it from other structures, such as the vertebrae, cerebrospinal fluid, and tumors.

Recognition of bird species based on spike model using bird dataset.

Birds have often been recognised as the first informants of climatic change in our environment. Bird species recognition has assumed great significance not just for checking the survival of birds but also as an early warning signal of the declining health of earth and its climate. Earlier researchers have established recognition of bird species based on sounds from repository available online which were region-specific.