AI Medical Compendium Journal:
International journal of computer assisted radiology and surgery

Showing 11 to 20 of 481 articles

Multi-modal dataset creation for federated learning with DICOM-structured reports.

International journal of computer assisted radiology and surgery Feb 3, 2025
Purpose Federated training is often challenging on heterogeneous datasets due to divergent data storage options, inconsistent naming schemes, varied annotation procedures, and disparities in label quality. This is particularly evident in the emerging...
Humans Datasets as Topic Radiology Information Systems Federated Learning Deep Learning Electrocardiography Tomography, X-Ray Computed
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DenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation.

International journal of computer assisted radiology and surgery Jan 23, 2025
PURPOSE: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for se...
Image Processing, Computer-Assisted Anatomic Landmarks Heart Lung Deep Learning Semantics Radiography, Thoracic Humans Neural Networks, Computer
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Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture.

International journal of computer assisted radiology and surgery Jan 20, 2025
PURPOSE: Pulmonary perfusion imaging is a key lung health indicator with clinical utility as a diagnostic and treatment planning tool. However, current nuclear medicine modalities face challenges like low spatial resolution and long acquisition times...
Perfusion Imaging Four-Dimensional Computed Tomography Tomography, X-Ray Computed Lung Male Humans Deep Learning Female Middle Aged Supervised Machine Learning
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Attention-guided erasing for enhanced transfer learning in breast abnormality classification.

International journal of computer assisted radiology and surgery Jan 15, 2025
PURPOSE: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, att...
Machine Learning Female Humans Breast Breast Neoplasms Contrast Media Mammography Middle Aged Radiographic Image Interpretation, Computer-Assisted
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A real-time approach for surgical activity recognition and prediction based on transformer models in robot-assisted surgery.

International journal of computer assisted radiology and surgery Jan 12, 2025
PURPOSE: This paper presents a deep learning approach to recognize and predict surgical activity in robot-assisted minimally invasive surgery (RAMIS). Our primary objective is to deploy the developed model for implementing a real-time surgical risk m...
Robotic Surgical Procedures Humans Gestures Deep Learning Minimally Invasive Surgical Procedures
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G-SET-DCL: a guided sequential episodic training with dual contrastive learning approach for colon segmentation.

International journal of computer assisted radiology and surgery Jan 9, 2025
PURPOSE: This article introduces a novel deep learning approach to substantially improve the accuracy of colon segmentation even with limited data annotation, which enhances the overall effectiveness of the CT colonography pipeline in clinical settin...
Deep Learning Imaging, Three-Dimensional Colonic Polyps Colonography, Computed Tomographic Radiographic Image Interpretation, Computer-Assisted Algorithms Reproducibility of Results Colon Humans
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Comparison of active learning algorithms in classifying head computed tomography reports using bidirectional encoder representations from transformers.

International journal of computer assisted radiology and surgery Jan 8, 2025
PURPOSE: Systems equipped with natural language (NLP) processing can reduce missed radiological findings by physicians, but the annotation costs are burden in the development. This study aimed to compare the effects of active learning (AL) algorithms...
Tomography, X-Ray Computed Natural Language Processing Supervised Machine Learning Humans Algorithms Problem-Based Learning Head Radiology Information Systems
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Sparse keypoint segmentation of lung fissures: efficient geometric deep learning for abstracting volumetric images.

International journal of computer assisted radiology and surgery Jan 7, 2025
PURPOSE: Lung fissure segmentation on CT images often relies on 3D convolutional neural networks (CNNs). However, 3D-CNNs are inefficient for detecting thin structures like the fissures, which make up a tiny fraction of the entire image volume. We pr...
Humans Neural Networks, Computer Deep Learning Tomography, X-Ray Computed Imaging, Three-Dimensional Lung Radiographic Image Interpretation, Computer-Assisted
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Multi-institutional development and testing of attention-enhanced deep learning segmentation of thyroid nodules on ultrasound.

International journal of computer assisted radiology and surgery Jan 3, 2025
PURPOSE: Thyroid nodules are common, and ultrasound-based risk stratification using ACR's TIRADS classification is a key step in predicting nodule pathology. Determining thyroid nodule contours is necessary for the calculation of TIRADS scores and ca...
Thyroid Nodule Image Interpretation, Computer-Assisted Deep Learning Ultrasonography Humans Retrospective Studies Algorithms Female Male
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Leveraging domain knowledge for synthetic ultrasound image generation: a novel approach to rare disease AI detection.

International journal of computer assisted radiology and surgery Dec 29, 2024
PURPOSE: This study explores the use of deep generative models to create synthetic ultrasound images for the detection of hemarthrosis in hemophilia patients. Addressing the challenge of sparse datasets in rare disease diagnostics, the study aims to ...
Hemophilia A Artificial Intelligence Humans Hemarthrosis Ultrasonography Rare Diseases Neural Networks, Computer Image Interpretation, Computer-Assisted
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