Optimized approach to image-based automatic disease classification using improved capsule networks

Automatic multiple disease prediction approach using optimized convolutional neural network layers

Deep Learning-Based Medical Image Classification Using Convolutional Neural Networks for Clinical Diagnosis

The findings indicate that the proposed CNN provides highly accurate and reliable medical image classification, making it a promising decision-support tool for early pneumonia detection and improved clinical diagnosis.

A medical image classification algorithm based on a hierarchical and complementary attention-enhanced Swin Transformer model

Comparisons across all datasets confirm that the proposed framework exhibits strong robustness and generalization capability when processing multiple medical imaging modalities, thereby providing reliable technical support for computer-aided medical diagnosis systems.

Attention-Guided Mask R-CNN for Liver Tumor Segmentation and Classification from CT Scans: A Tailored Approach

An attention-controlled automated liver tumor segmentation and classification based on a customized Mask Region Convolutional Neural Network with an addition of Multi-Scale Attention Gate (MSAG) is introduced with affirm the usefulness and clinical appropriateness of the suggested framework.

Deep learning-based automated brain tumor detection using a proposed convolutional neural network architecture

Brain tumors pose a critical threat to human health, often resulting in significant neurological impairments and high mortality rates. Early and accurate detection is essential for improving patient outcomes; however, conventional diagnostic methods, such as magnetic resonance imaging (MRI) interpretation by radiologis...

An Efficient Hybrid Framework for Multiclass Brain Tumor Classification Using Handcrafted Features and Neural Networks

Brain tumors are serious neurological disorders characterized by abnormal and uncontrolled cell growth within brain tissues, leading to significant disruption of normal brain function. Early detection is essential for improving clinical outcomes and enabling effective treatment. Medical imaging techniques, particularly...