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

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 ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
Search Engine Land

Google updates image SEO best practices to say use the same image URL for same image across your pages

Google updated its Google image SEO best practices help document to recommend that you use the same image file name URL for the same image, even if you place that same image on different pages on your ...
IEEE

A Method of Debris Image Segmentation Based on SVM

Abstract: This paper realizes debris image segmentation using SVM. First we consider image segmentation as a pixel classification problem, and then build a SVM to solve the classification problem.