AIMC Topic: Image Interpretation, Computer-Assisted

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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 Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Bone and Bones Magnetic Resonance Imaging Humans Algorithms
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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 Retrospective Studies Female Brain Neoplasms Image Interpretation, Computer-Assisted Deep Learning Aged Male Organometallic Compounds Adult Contrast Media Middle Aged Sensitivity and Specificity Magnetic Resonance Imaging
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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...
Magnetic Resonance Imaging Placenta Pre-Eclampsia Adult Humans Image Interpretation, Computer-Assisted Retrospective Studies Radiomics Fetal Growth Retardation Deep Learning Pregnancy Female
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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...
Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Graph Neural Networks Female Breast Neoplasms ROC Curve
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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...
Neural Networks, Computer Elastic Modulus Humans Algorithms Elasticity Imaging Techniques Image Interpretation, Computer-Assisted Reproducibility of Results Computer Simulation Magnetic Resonance Imaging Signal-To-Noise Ratio Phantoms, Imaging
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Advances in colorectal cancer diagnosis using optimal deep feature fusion approach on biomedical images.

Scientific reports Feb 4, 2025
Colorectal cancer (CRC) is the second popular cancer in females and third in males, with an increased number of cases. Pathology diagnoses complemented with predictive and prognostic biomarker information is the first step for personalized treatment....
Male Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Algorithms Female Colorectal Neoplasms Artificial Intelligence Machine Learning Humans
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IPNet: An Interpretable Network With Progressive Loss for Whole-Stage Colorectal Disease Diagnosis.

IEEE transactions on medical imaging Feb 4, 2025
Colorectal cancer plays a dominant role in cancer-related deaths, primarily due to the absence of obvious early-stage symptoms. Whole-stage colorectal disease diagnosis is crucial for assessing lesion evolution and determining treatment plans. Howeve...
Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Colorectal Neoplasms Humans
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M₂DC: A Meta-Learning Framework for Generalizable Diagnostic Classification of Major Depressive Disorder.

IEEE transactions on medical imaging Feb 4, 2025
Psychiatric diseases are bringing heavy burdens for both individual health and social stability. The accurate and timely diagnosis of the diseases is essential for effective treatment and intervention. Thanks to the rapid development of brain imaging...
Humans Machine Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Neuroimaging Algorithms Brain Depressive Disorder, Major
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Cohort-Individual Cooperative Learning for Multimodal Cancer Survival Analysis.

IEEE transactions on medical imaging Feb 4, 2025
Recently, we have witnessed impressive achievements in cancer survival analysis by integrating multimodal data, e.g., pathology images and genomic profiles. However, the heterogeneity and high dimensionality of these modalities pose significant chall...
Neoplasms Multimodal Imaging Survival Analysis Algorithms Image Interpretation, Computer-Assisted Humans Female Male Machine Learning
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GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentation.

IEEE transactions on medical imaging Feb 4, 2025
Histopathological image segmentation is a laborious and time-intensive task, often requiring analysis from experienced pathologists for accurate examinations. To reduce this burden, supervised machine-learning approaches have been adopted using large...
Databases, Factual Supervised Machine Learning Image Interpretation, Computer-Assisted Humans Algorithms
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