IEEE

Medical Image Segmentation Using Deep Learning and Transformers

Abstract: Deep learning models, including convolutional neural networks (CNNs) and transformer-based architectures, have achieved remarkable results in medical image segmentation tasks. However, the ...
IEEE

Indian Sign Language Detection for Real-Time Translation using Machine Learning

Abstract: Gestural Language used by deaf and mute communities to communicate by using hand gestures and body movements that rely on visual and spatial patterns known as sign languages. Communication ...
IEEE

Deep Learning-Enhanced Ultrasound Analysis: Classifying Breast Tumors Using Segmentation and Feature Extraction

Abstract: Breast cancer remains a significant global health challenge, requiring accurate and effective diagnostic methods for timely treatment. Ultrasound imaging is a valuable diagnostic tool for ...
IEEE

An Evaluation of Medical Image Analysis using Image Segmentation and Deep Learning Techniques for Brain-Tumour

Abstract: An aberrant mass of rapidly proliferating brain cells, known as a brain tumour, may develop into various forms of cancer. The segmentation of brain tumours by MRI scans is a challenging but ...
IEEE

ECHO-SegNet Framework for Accurate 2D Echocardiographic Image Segmentation Using the CAMUS Dataset

Abstract: Accurate segmentation of cardiac structures in echocardiographic images plays a vital role in the quantitative assessment of cardiac function, enabling early detection and management of ...
IEEE

Detection of Bone Cancer using Machine Learning: A Multi-Model Approach

Abstract: Bone cancer diagnosis remains a critical challenge due to the intricate nature of medical imaging data and the need for precise interpretation. This study introduces a machine learning ...
SciELO

Artificial intelligence in the diagnosis and management of dysphagia: a scoping review

Purpose This scoping review aimed to map and synthesize evidence on technological advancements using Artificial Intelligence in the diagnosis and management of dysphagia. We followed the PRISMA ...
IEEE

Brain MRI Analysis Using CNN-Based Feature Extraction and Machine Learning Techniques to Diagnose Alzheimer's Disease

Abstract: This research focuses on developing a complex framework for automatic diagnosis purposes of Alzheimer's disease from MRI brain data, with emphasis placed on advancement in accuracy towards ...
IEEE

3D Reconstruction of Steel Rail using Multi-view Cameras and Mask R-CNN

Abstract: This study proposed a method that integrates multi-view image processing, depth estimation, and point cloud generation to accurately reconstruct a 3D model of a rail. The method is tested by ...
IEEE

Detection of Single Radio Isotopes Using Mask CNN Approach

Abstract: The detection of radioisotopes via the use of a plastic scintillation detector presents a substantial difficulty. This is mostly owing to the low cross-sections and poor spectrum resolution ...
IEEE

Cartoonification of the Real Image Using Machine Learning

Abstract: The proposed work highlights the transformation of general pictures to cartoon-like images based on recent computer vision methodologies. This work develops and refines techniques for ...
IEEE

A Novel Deep Learning-Based Approach for Brain Tumor Segmentation and Classification Using Diffusion-Weighted Imaging and Magnetic Resonance Spectroscopy

Abstract: Brain tumours (BT) are a dangerous condition that gets a lot of attention. They can be fatal. However, for effective treatment and life-saving measures, early detection and tumour type and ...