IEEE

PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification

Abstract: In recent years, supervised learning using convolutional neural networks (CNN) has served as a benchmark for various medical image segmentation and classification. However, supervised ...
Frontiers

Analytical computation for segmentation and classification of lumbar vertebral fractures

Spinal health forms the cornerstone of the overall human body functionality with the lumbar spine playing a critical role and prone to various types of injuries due to inflammation and diseases, ...
IEEE

ZSG-Net: A Zero-Shot Super-Resolution Guided Network for Ultrasound Image Segmentation and Classification

Abstract: Automated ultrasound (US) image analysis is hindered by challenges stemming from low resolution, noise, and non-uniform grayscale distribution, which compromise image quality. While many ...
Frontiers

Carotid plaque segmentation and classification using MRI-based plaque texture analysis and convolutional neural network

Background: Accurate segmentation and classification of carotid plaques are critical for assessing stroke risk. However, conventional methods are hindered by manual intervention, inter-observer ...
Scientific Research Publishing

Research on the Design of News Text Classification Algorithm Based on Bidirectional GRU Neural Network ()

School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China. This study aims to design and implement an efficient news text classification system based on deep learning to ...