AIMC Topic: Magnetic Resonance Imaging

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CNN-based glioma detection in MRI: A deep learning approach.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: More than a million people are affected by brain tumors each year; high-grade gliomas (HGGs) and low-grade gliomas (LGGs) present serious diagnostic and treatment hurdles, resulting in shortened life expectancies. Glioma segmentation is s...

Classifying Alzheimer's Disease Neuropathology Using Clinical and MRI Measurements.

Journal of Alzheimer's disease : JAD
BACKGROUND: Computer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack...

Improving Efficiency of Brain Tumor Classification Models Using Pruning Techniques.

Current medical imaging
BACKGROUND: This research investigates the impact of pruning on reducing the computational complexity of a five-layered Convolutional Neural Network (CNN) designed for classifying MRI brain tumors. The study focuses on enhancing the efficiency of the...

Updated Models of Alzheimer's Disease with Deep Neural Networks.

Journal of Alzheimer's disease : JAD
BACKGROUND: In recent years, researchers have focused on developing precise models for the progression of Alzheimer's disease (AD) using deep neural networks. Forecasting the progression of AD through the analysis of time series data represents a pro...

Evaluation of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Using MR Images and Deep Learning Neural Networks.

Current medical imaging
INTRODUCTION: The aim of the study was to develop deep-learning neural networks to guide treatment decisions and for the accurate evaluation of tumor response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using magnetic resonance (MR) imag...

Enhancing Alzheimer's Disease Classification with Transfer Learning: Finetuning a Pre-trained Algorithm.

Current medical imaging
OBJECTIVE: The increasing longevity of the population has made Alzheimer's disease (AD) a significant public health concern. However, the challenge of accurately distinguishing different disease stages due to limited variability within the same stage...

Prostate Segmentation in MRI Images using Transfer Learning based Mask RCNN.

Current medical imaging
INTRODUCTION: The second highest cause of death among males is Prostate Cancer (PCa) in America. Over the globe, it's the usual case in men, and the annual PCa ratio is very surprising. Identical to other prognosis and diagnostic medical systems, dee...

Brain tumor segmentation based on the U-NET+⁣+ network with efficientnet encoder.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Brain tumor is a highly destructive, aggressive, and fatal disease. The presence of brain tumors can disrupt the brain's ability to control body movements, consciousness, sensations, thoughts, speech, and memory. Brain tumors are often ac...

A Systematic Review on Deep Learning Model in Computer-aided Diagnosis for Anterior Cruciate Ligament Injury.

Current medical imaging
INTRODUCTION: In developing Computer-Aided Diagnosis (CAD), a Convolutional Neural Network (CNN) has been commonly used as a Deep Learning (DL) model. Although it is still early, DL has excellent potential in implementing computers in medical diagnos...

Convolutional Neural Networks for Glioma Segmentation and Prognosis: A Systematic Review.

Critical reviews in oncogenesis
Deep learning (DL) is poised to redefine the way medical images are processed and analyzed. Convolutional neural networks (CNNs), a specific type of DL architecture, are exceptional for high-throughput processing, allowing for the effective extractio...