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 ...
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

Explore the Use of Prompt-Based LLM for Credit Risk Classification ()

Credit risk assessment plays an important role in financial services by estimating the chance of a borrower defaulting. Recently, although the Large Language Models (LLMs) have demonstrated superior ...
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 ...