AIMC Topic: Image Interpretation, Computer-Assisted

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Will Transformers change gastrointestinal endoscopic image analysis? A comparative analysis between CNNs and Transformers, in terms of performance, robustness and generalization.

Medical image analysis Sep 16, 2024
Gastrointestinal endoscopic image analysis presents significant challenges, such as considerable variations in quality due to the challenging in-body imaging environment, the often-subtle nature of abnormalities with low interobserver agreement, and ...
Endoscopy, Gastrointestinal Esophageal Neoplasms Image Interpretation, Computer-Assisted Barrett Esophagus Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Humans
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CBAM-RIUnet: Breast Tumor Segmentation With Enhanced Breast Ultrasound and Test-Time Augmentation.

Ultrasonic imaging Sep 16, 2024
This study addresses the challenge of precise breast tumor segmentation in ultrasound images, crucial for effective Computer-Aided Diagnosis (CAD) in breast cancer. We introduce CBAM-RIUnet, a deep learning (DL) model for automated breast tumor segme...
Humans Breast Image Interpretation, Computer-Assisted Female Breast Neoplasms Deep Learning Ultrasonography, Mammary
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Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Sep 16, 2024
(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Resonance Angiography (MRA) is frequently used for the screening of UIAs due to its high resolution in ...
Observer Variation Magnetic Resonance Angiography Intracranial Aneurysm Magnetic Resonance Imaging Predictive Value of Tests Radiologists Image Interpretation, Computer-Assisted Humans Female Reproducibility of Results Aged Adult Male Middle Aged Deep Learning
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Clinical feasibility of deep learning-accelerated single-shot turbo spin echo sequence with enhanced denoising for pancreas MRI at 3 Tesla.

European journal of radiology Sep 15, 2024
PURPOSE: To assess the feasibility of the single-shot turbo spin echo sequence using deep learning-based reconstruction (DLR) (HASTE) with enhanced denoising for pancreas MRI.
Humans Pancreatic Neoplasms Feasibility Studies Male Image Interpretation, Computer-Assisted Image Enhancement Pancreas Retrospective Studies Middle Aged Signal-To-Noise Ratio Deep Learning Pancreatic Cyst Female Magnetic Resonance Imaging Aged Adult
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Multiparametric MRI-based radiomics combined with 3D deep transfer learning to predict cervical stromal invasion in patients with endometrial carcinoma.

Abdominal radiology (New York) Sep 14, 2024
OBJECTIVE: To develop and compare various preoperative cervical stromal invasion (CSI) prediction models, including radiomics, three-dimensional (3D) deep transfer learning (DTL), and integrated models, using single-sequence and multiparametric MRI.
Image Interpretation, Computer-Assisted Endometrial Neoplasms Multiparametric Magnetic Resonance Imaging Female Magnetic Resonance Imaging Humans Aged Cervix Uteri Retrospective Studies Adult Neoplasm Invasiveness Middle Aged Radiomics Predictive Value of Tests Deep Learning Imaging, Three-Dimensional Contrast Media
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Deep learning constrained compressed sensing reconstruction improves high-resolution three-dimensional (3D) T2-weighted turbo spin echo magnetic resonance imaging (MRI) of the lumbar spine.

Clinical radiology Sep 14, 2024
AIM: We sought to assess the image quality of three-dimensional (3D) T2-weighted (T2w) turbo spin echo (TSE) sequences with deep learning (DL)-constrained compressed sensing (CS) reconstruction relative to a reference two-dimensional (2D) T2w TSE seq...
Male Middle Aged Deep Learning Imaging, Three-Dimensional Magnetic Resonance Imaging Lumbar Vertebrae Image Interpretation, Computer-Assisted Female Aged Aged, 80 and over Adult Humans
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Enhancing reginal wall abnormality detection accuracy: Integrating machine learning, optical flow algorithms, and temporal convolutional networks in multi-view echocardiography.

PloS one Sep 12, 2024
BACKGROUND: Regional Wall Motion Abnormality (RWMA) serves as an early indicator of myocardial infarction (MI), the global leader in mortality. Accurate and early detection of RWMA is vital for the successful treatment of MI. Current automated echoca...
Humans Heart Ventricles Image Interpretation, Computer-Assisted Male Echocardiography Deep Learning Myocardial Infarction Neural Networks, Computer Machine Learning Algorithms Female
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Automated biventricular quantification in patients with repaired tetralogy of Fallot using a three-dimensional deep learning segmentation model.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Sep 11, 2024
BACKGROUND: Deep learning is the state-of-the-art approach for automated segmentation of the left ventricle (LV) and right ventricle (RV) in cardiovascular magnetic resonance (CMR) images. However, these models have been mostly trained and validated ...
Tetralogy of Fallot Cardiac Surgical Procedures Male Child Heart Ventricles Female Imaging, Three-Dimensional Magnetic Resonance Imaging, Cine Image Interpretation, Computer-Assisted Ventricular Function, Left Humans Ventricular Function, Right Databases, Factual Automation Treatment Outcome Retrospective Studies Predictive Value of Tests Reproducibility of Results Young Adult Adult Deep Learning Adolescent
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Image-Based Artificial Intelligence in Psoriasis Assessment: The Beginning of a New Diagnostic Era?

American journal of clinical dermatology Sep 11, 2024
Psoriasis, a chronic inflammatory skin disease, affects millions of people worldwide. It imposes a significant burden on patients' quality of life and healthcare systems, creating an urgent need for optimized diagnosis, treatment, and management. In ...
Humans Severity of Illness Index Psoriasis Skin Image Interpretation, Computer-Assisted Artificial Intelligence Machine Learning Algorithms Quality of Life
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Towards explainable oral cancer recognition: Screening on imperfect images via Informed Deep Learning and Case-Based Reasoning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 11, 2024
Oral squamous cell carcinoma recognition presents a challenge due to late diagnosis and costly data acquisition. A cost-efficient, computerized screening system is crucial for early disease detection, minimizing the need for expert intervention and e...
Humans Artificial Intelligence Mouth Neoplasms Image Interpretation, Computer-Assisted Carcinoma, Squamous Cell Deep Learning Early Detection of Cancer
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