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Image Interpretation, Computer-Assisted

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A deep learning detection method for pancreatic cystic neoplasm based on Mamba architecture.

Journal of X-ray science and technology
OBJECTIVE: Early diagnosis of pancreatic cystic neoplasm (PCN) is crucial for patient survival. This study proposes M-YOLO, a novel model combining Mamba architecture and YOLO, to enhance the detection of pancreatic cystic tumors. The model addresses...

FusionNet: Dual input feature fusion network with ensemble based filter feature selection for enhanced brain tumor classification.

Brain research
Brain tumors pose a significant threat to human health, require a precise and quick diagnosis for effective treatment. However, achieving high diagnostic accuracy with traditional methods remains challenging due to the complex nature of brain tumors....

An 8-point scale lung ultrasound scoring network fusing local detail and global features.

Scientific reports
Manual lung ultrasound (LUS) scoring is influenced by clinicians' subjective interpretation, leading to potential inconsistencies and misdiagnoses due to varying levels of experience. To improve monitoring of pulmonary ventilation and support early d...

Z-SSMNet: Zonal-aware Self-supervised Mesh Network for prostate cancer detection and diagnosis with Bi-parametric MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Bi-parametric magnetic resonance imaging (bpMRI) has become a pivotal modality in the detection and diagnosis of clinically significant prostate cancer (csPCa). Developing AI-based systems to identify csPCa using bpMRI can transform prostate cancer (...

Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence: Results of Hand-Crafted, Deep Radiomics Features and Radiologists' Assessment in Multicenter Cohorts.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVE: To develop, test, and externally validate a hybrid artificial intelligence (AI) model based on hand-crafted and deep radiomics features extracted from B-mode ultrasound images in differentiating benign and malignant thyroid nodules compare...

Artificial Intelligence in Spine Imaging: A Paradigm Shift in Diagnosis and Care.

Magnetic resonance imaging clinics of North America
Recent advancements in artificial intelligence (AI) can significantly improve radiologists' workflow, improving efficiency and diagnostic accuracy. Current AI applications within spine imaging are approved to accelerate image acquisition time, improv...

A Bi-modal Temporal Segmentation Network for Automated Segmentation of Focal Liver Lesions in Dynamic Contrast-enhanced Ultrasound.

Ultrasound in medicine & biology
OBJECTIVE: To develop and validate an automated deep learning-based model for focal liver lesion (FLL) segmentation in a dynamic contrast-enhanced ultrasound (CEUS) video.

VSR-Net: Vessel-Like Structure Rehabilitation Network With Graph Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The morphologies of vessel-like structures, such as blood vessels and nerve fibres, play significant roles in disease diagnosis, e.g., Parkinson's disease. Although deep network-based refinement segmentation and topology-preserving segmentation metho...

A quantitatively interpretable model for Alzheimer's disease prediction using deep counterfactuals.

NeuroImage
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions. Counterfactual reasoning has rec...

Detection of brain tumors using a transfer learning-based optimized ResNet152 model in MR images.

Computers in biology and medicine
Brain tumors are incredibly harmful and can drastically reduce life expectancy. Most researchers use magnetic resonance (MR) scans to detect tumors because they can provide detailed images of the affected area. Recently, AI-based deep learning method...