Efficient Multiple Organ Localization in CT Image Using 3D Region Proposal Network

A light CNN for detecting COVID-19 from CT scans of the chest

“…Deep Learning methods have been extensively used in medical imaging. In particular, convolutional neural networks (CNNs) have been used both for classification and segmentation problems, also of CT images [16] . However, CT images of the lungs referred to COVID-19 and not COVID-19 can be easily misclassified especially when damages due to pneumonia referred due to different causes are present at the same time.…”

Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet

“…Recent advances in artificial intelligence and computer vision lead to a rapid development of deep learning technology [1] in medical image analysis and digital medicine [2] , [3] , [4] , [5] , [6] , [7] . With end-to-end learning of deep representation, deep supervised learning, as a unified methodology, achieved remarkable success in numerous 2D and 3D medical image tasks, e.g., classification [8] , detection [9] , segmentation [10] . With the rise of deep learning, infrastructures, algorithms and data (with annotations) are known to be the keys to its success.…”

Magnetic Resonance Image Segmentation Based on Multi-Scale Convolutional Neural Network

“…The basic idea of region growing is to group pixels with similar properties to form regions. Specifically, a seed pixel is found as a growth starting point for each region that needs to be segmented, and then pixels having the same or similar properties as the seed pixels in the field around the seed pixel are merged into the region where the seed pixel is located [38]. These new pixels are treated as seed pixels to continue the above process until no more pixels satisfying the condition can be included, so that an area becomes long.…”