AIMC Topic: Image Interpretation, Computer-Assisted

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[Feature distillation multiple instance learning method based on sequence reorganized Mamba].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Prostate cancer is one of the most prevalent malignancies among men worldwide, and its diagnosis relies heavily on accurate analysis of whole slide imaging (WSI) in histopathology. However, manual interpretation is time-consuming and prone to inconsi...

Ultrasound image-based contrastive fusion non-invasive liver fibrosis staging algorithm.

Abdominal radiology (New York)
OBJECTIVE: The diagnosis of liver fibrosis is usually based on histopathological examination of liver puncture specimens. Although liver puncture is accurate, it has invasive risks and high economic costs, which are difficult for some patients to acc...

Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI.

IEEE transactions on bio-medical engineering
OBJECTIVE: Dynamic magnetic resonance imaging (MRI) plays an indispensable role in cardiac diagnosis. To enable fast imaging, the k-space data can be undersampled but the image reconstruction poses a great challenge of high-dimensional processing. Th...

Applications of artificial intelligence in abdominal imaging.

Abdominal radiology (New York)
The rapid advancements in artificial intelligence (AI) carry the promise to reshape abdominal imaging by offering transformative solutions to challenges in disease detection, classification, and personalized care. AI applications, particularly those ...

Research-based clinical deployment of artificial intelligence algorithm for prostate MRI.

Abdominal radiology (New York)
PURPOSE: A critical limitation to deployment and utilization of Artificial Intelligence (AI) algorithms in radiology practice is the actual integration of algorithms directly into the clinical Picture Archiving and Communications Systems (PACS). Here...

A Joint Geometric Topological Analysis Network (JGTA-Net) for Detecting and Segmenting Intracranial Aneurysms.

IEEE transactions on bio-medical engineering
OBJECTIVE: The rupture of intracranial aneurysms leads to subarachnoid hemorrhage. Detecting intracranial aneurysms before rupture and stratifying their risk is critical in guiding preventive measures. Point-based aneurysm segmentation provides a pla...

Utility of Thin-slice Single-shot T2-weighted MR Imaging with Deep Learning Reconstruction as a Protocol for Evaluating Pancreatic Cystic Lesions.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: To assess the effects of industry-developed deep learning reconstruction with super resolution (DLR-SR) on single-shot turbo spin-echo (SshTSE) images with thickness of 2 mm with DLR (SshTSE) relative to those of images with a thickness of 5...

Deep learning model for automated detection of Helicobacter pylori and intestinal metaplasia on gastric biopsy digital whole slide images.

American journal of clinical pathology
OBJECTIVE: To develop an automated detection tool for Helicobacter pylori (HP) microorganisms (HPOrg) and intestinal metaplasia (IM) identification on gastric biopsy specimens on hematoxylin and eosin (H&E) whole-slide images (WSIs), incorporating ba...

Pix2Pix generative-adversarial network in improving the quality of T2-weighted prostate magnetic resonance imaging: a multi-reader study.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: To assess the performance and feasibility of generative deep learning in enhancing the image quality of T2-weighted (T2W) prostate magnetic resonance imaging (MRI).