Two-stage deep learning for segmenting in concrete X-ray CT images

Automatic Coronary Artery Segmentation in X-ray Angiograms

Filip Filipović, Tijana Geroski, N Filipovic

Coronary artery disease is one of the leading causes of morbidity and mortality worldwide, with X-ray coronary angiography serving as the clinical gold standard for diagnosis and intervention planning. Accurate segmentation of coronary arteries is essential for quantitative analy…Read more

Code for: Investigating Osteoporosis Diagnosis Using Clinical and Hip X-Ray Data from the Syrian Population

Sweekat Kholoud

This repository contains the Python implementation used in the study "Investigating Osteoporosis Diagnosis Using Clinical and Hip X-Ray Data from the Syrian Population". The notebook implements the complete experimental workflow described in the manuscript, including clinical mac…Read more

# Artificial Intelligence-Enabled Quantification of Cube and Goss Textures in Polycrystalline Materials: A Comprehensive Review of Machine Learning, Deep Learning, and EBSD-Based Characterization Approaches

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…Read more

AI-based Pathology Detection and Localization in Chest X-Ray Using Parallelized Multiple DCNN

B M Chandrakala, B P Pradeep Kumar, Bimba Prasad, Preethi Lokesh, R Girija, E Prathibha

Radiography, renowned for its diagnostic prowess and affordability, plays a key role in detecting diseases, including critical conditions. Chest radiography, focusing on a vital body area, poses interpretational challenges, necessitating experienced radiologists for accurate diag…Read more

Low Dose and High Contrast Biomedical Imaging Using SelfSupervised Deep Learning

Xiao Fan Ding, Xiaoman Duan, Ning Zhu

Self-supervised deep learning has emerged as a powerful method for image enhancement when a priori ground-truth references are not available. Stemming from Noise2Noise , it was shown that a convolutional neural network (CNN) can be trained from a noisy input and target pair of th…Read more

Also available via: European Organization for Nuclear Research

Automated Detection of Self-Harm Wounds Using Deep Learning and Image Processing in Forensic Medicine

A Mohammadi, Mahdi Mehrabi, Seyed Mohammad Saadatneshan, Kamroz Amini, Mahdi Gheysari

Background and Objective: Self-harm is a psychologically damaging behavior, and its accurate differentiation from other wounds (violence, accidents, burns, diabetic ulcers) is critically important in forensic medicine. However, this differentiation often falls into a diagnostic "…Read more