A PCCN-Based Centered Deep Learning Process for Segmentation of Spine and Heart
Kasi Uday Kiran, Gowtham Mamidisetti, Chandra Shaker Pittala, Vallabhuni Vijay, Rajeev Ratna Vallabhuni · Advances in social networking and online communities book series · 2022
The spinal cord and heart in the body are major organs. Diagnosis of diseases in these organs is very complex using MRI and CT images. The conventional methods like post segmentation, pre-image processing, and text feature extraction mechanisms cannot handle accurate diagnosis. Therefore, advanced techniques are needed. In this work, pixel-based convolution neural networks with centered deep learning processes are proposed to cross over the problems. The projected PCNN has four pixel-based convolution neural networks. Here disease objects are identified through grading framework. The entire mechanism is working based on sequential part of PCNN segmentation process. The spinal cord and heart image MRI-based diagnosis process is very difficult with conventional methods. But the proposed method provides accurate results and outperforms the standard methodology performance measures in accuracy, precision, and F1score.