AIMC Topic: Image Interpretation, Computer-Assisted

Clear Filters Showing 81 to 90 of 3033 articles

Accurate and real-time brain tumour detection and classification using optimized YOLOv5 architecture.

Scientific reports
The brain tumours originate in the brain or its surrounding structures, such as the pituitary and pineal glands, and can be benign or malignant. While benign tumours may grow into neighbouring tissues, metastatic tumours occur when cancer from other ...

BIScreener: enhancing breast cancer ultrasound diagnosis through integrated deep learning with interpretability.

Analytical methods : advancing methods and applications
Breast cancer is the leading cause of death among women worldwide, and early detection through the standardized BI-RADS framework helps physicians assess the risk of malignancy and guide appropriate diagnostic and treatment decisions. In this study, ...

Diabetic retinopathy detection using adaptive deep convolutional neural networks on fundus images.

Scientific reports
Diabetic retinopathy (DR) is an age-related macular degeneration eye disease problem that causes pathological changes in the retinal neural and vascular system. Recently, fundus imaging is a popular technology and widely used for clinical diagnosis, ...

Deep learning-based automatic detection and grading of disk herniation in lumbar magnetic resonance images.

Scientific reports
Magnetic resonance imaging of the lumbar spine is a key technique for clarifying the cause of disease. The greatest challenges today are the repetitive and time-consuming process of interpreting these complex MR images and the problem of unequal diag...

A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images.

Scientific reports
Breast cancer remains a significant global health challenge among women, with histopathological image analysis playing a critical role in early detection. However, existing diagnostic models often struggle to extract complex patterns from high-resolu...

ColoViT: a synergistic integration of EfficientNet and vision transformers for advanced colon cancer detection.

Journal of cancer research and clinical oncology
BACKGROUND: Colon cancer remains a leading cause of cancer-related mortality globally, highlighting the urgent need for advanced diagnostic methods to improve early detection and patient outcomes.

Explainable deep learning approaches for high precision early melanoma detection using dermoscopic images.

Scientific reports
Detecting skin melanoma in the early stage using dermoscopic images presents a complex challenge due to the inherent variability in images. Utilizing dermatology datasets, the study aimed to develop Automated Diagnostic Systems for early skin cancer ...

Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI.

Scientific reports
Robust differentiation between infarcted and normal myocardial tissue is essential for improving diagnostic accuracy and personalizing treatment in myocardial infarction (MI). This study proposes a hybrid framework combining radiomic texture analysis...

Hierarchical attention fusion of EUS-doppler features for GISTs risk assessment.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Assessing the preoperative malignancy risk of gastrointestinal stromal tumors (GISTs) is crucial for determining the appropriate treatment plan and prognosis. The current automated diagnosis of GISTs based on endoscopic ultrasound (EUS) pose challeng...

The case for homebrew AI in diagnostic pathology.

The Journal of pathology
Artificial intelligence (AI) methods for digital pathology have tremendous potential to improve cancer diagnostics, biomarkers, and ultimately patient care. These AI methods, if marketed and sold, require authorisation or clearance as in vitro diagno...