AIMC Topic: Image Interpretation, Computer-Assisted

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Deep Learning Reconstruction Combined With Conventional Acceleration Improves Image Quality of 3 T Brain MRI and Does Not Impact Quantitative Diffusion Metrics.

Investigative radiology Feb 7, 2025
OBJECTIVES: Deep learning reconstruction of magnetic resonance imaging (MRI) allows to either improve image quality of accelerated sequences or to generate high-resolution data. We evaluated the interaction of conventional acceleration and Deep Resol...
Prospective Studies Brain Female Aged Humans Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Artifacts Diffusion Magnetic Resonance Imaging Adult Male Middle Aged Deep Learning Echo-Planar Imaging
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A novel deep learning framework for retinal disease detection leveraging contextual and local features cues from retinal images.

Medical & biological engineering & computing Feb 7, 2025
Retinal diseases are a serious global threat to human vision, and early identification is essential for effective prevention and treatment. However, current diagnostic methods rely on manual analysis of fundus images, which heavily depends on the exp...
Fundus Oculi Retina Image Interpretation, Computer-Assisted Retinal Diseases Algorithms Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification.

Scientific reports Feb 7, 2025
Accurately and early diagnosis of melanoma is one of the challenging tasks due to its unique characteristics and different shapes of skin lesions. So, in order to solve this issue, the current study examines various deep learning-based approaches and...
Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Dermoscopy Machine Learning Deep Learning Algorithms Melanoma Image Processing, Computer-Assisted Skin Neoplasms Bayes Theorem
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Diagnosis of Sacroiliitis Through Semi-Supervised Segmentation and Radiomics Feature Analysis of MRI Images.

Journal of magnetic resonance imaging : JMRI Feb 6, 2025
BACKGROUND: Sacroiliitis is a hallmark of ankylosing spondylitis (AS), and early detection plays an important role in managing the condition effectively. MRI is commonly used for diagnosing sacroiliitis, traditional methods often depend on subjective...
Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Edema Young Adult Sacroiliac Joint Adult Child Sensitivity and Specificity ROC Curve Image Processing, Computer-Assisted Radiomics Male Middle Aged Sacroiliitis Adolescent Retrospective Studies Female Reproducibility of Results Aged Humans Algorithms
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SegmentAnyBone: A universal model that segments any bone at any location on MRI.

Medical image analysis Feb 6, 2025
Magnetic Resonance Imaging (MRI) is pivotal in radiology, offering non-invasive and high-quality insights into the human body. Precise segmentation of the MRIs into different organs and tissues would be very beneficial as it would allow more accurate...
Image Processing, Computer-Assisted Humans Algorithms Magnetic Resonance Imaging Deep Learning Image Interpretation, Computer-Assisted Bone and Bones
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Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI.

European radiology experimental Feb 6, 2025
BACKGROUND: Gadolinium-enhanced "sampling perfection with application-optimized contrasts using different flip angle evolution" (SPACE) sequence allows better visualization of brain metastases (BMs) compared to "magnetization-prepared rapid acquisiti...
Humans Algorithms Middle Aged Deep Learning Contrast Media Magnetic Resonance Imaging Adult Image Interpretation, Computer-Assisted Sensitivity and Specificity Retrospective Studies Organometallic Compounds Brain Neoplasms Female Male Aged
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Deep learning-based breast cancer diagnosis in breast MRI: systematic review and meta-analysis.

European radiology Feb 5, 2025
OBJECTIVES: The aim of this work is to evaluate the performance of deep learning (DL) models for breast cancer diagnosis with MRI.
Breast Neoplasms Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Humans Female Sensitivity and Specificity
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Association between deep learning radiomics based on placental MRI and preeclampsia with fetal growth restriction: A multicenter study.

European journal of radiology Feb 5, 2025
PURPOSE: Preeclampsia (PE) is associated with placental insufficiency and could lead to adverse pregnancy outcomes. The study aimed to develop a placental T2-weighted image-based automatic quantitative model for the identification of PE pregnancies a...
Image Interpretation, Computer-Assisted Humans Fetal Growth Retardation Retrospective Studies Female Magnetic Resonance Imaging Pregnancy Adult Placenta Radiomics Pre-Eclampsia Deep Learning
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Breast cancer image classification based on H&E staining using a causal attention graph neural network model.

Medical & biological engineering & computing Feb 4, 2025
Breast cancer image classification remains a challenging task due to the high-resolution nature of pathological images and their complex feature distributions. Graph neural networks (GNNs) offer promising capabilities to capture local structural info...
Image Interpretation, Computer-Assisted Graph Neural Networks Humans Neural Networks, Computer Algorithms Female Breast Neoplasms ROC Curve Image Processing, Computer-Assisted
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Quantification of tissue stiffness with magnetic resonance elastography and finite difference time domain (FDTD) simulation-based spatiotemporal neural network.

Magnetic resonance imaging Feb 4, 2025
Quantification of tissue stiffness with magnetic resonance elastography (MRE) is an inverse problem that is sensitive to noise. Conventional methods for the purpose include direct inversion (DI) and local frequency estimation (LFE). In this study, we...
Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Phantoms, Imaging Elastic Modulus Elasticity Imaging Techniques Algorithms Computer Simulation Reproducibility of Results Magnetic Resonance Imaging Humans Neural Networks, Computer
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