AIMC Topic: Image Processing, Computer-Assisted

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Slim UNETR: Scale Hybrid Transformers to Efficient 3D Medical Image Segmentation Under Limited Computational Resources.

IEEE transactions on medical imaging Mar 5, 2024
Hybrid transformer-based segmentation approaches have shown great promise in medical image analysis. However, they typically require considerable computational power and resources during both training and inference stages, posing a challenge for reso...
Neural Networks, Computer Image Processing, Computer-Assisted
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Wavelet-Improved Score-Based Generative Model for Medical Imaging.

IEEE transactions on medical imaging Mar 5, 2024
The score-based generative model (SGM) has demonstrated remarkable performance in addressing challenging under-determined inverse problems in medical imaging. However, acquiring high-quality training datasets for these models remains a formidable tas...
Neural Networks, Computer Magnetic Resonance Imaging Artifacts Algorithms Signal-To-Noise Ratio Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm.

Journal of imaging informatics in medicine Mar 4, 2024
Coronary computed tomography angiography (CCTA) is an essential part of the diagnosis of chronic coronary syndrome (CCS) in patients with low-to-intermediate pre-test probability. The minimum technical requirement is 64-row multidetector CT (64-MDCT)...
Computed Tomography Angiography Middle Aged Coronary Vessels Coronary Angiography Humans Image Processing, Computer-Assisted Multidetector Computed Tomography Female Algorithms Artifacts Aged Male Deep Learning
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From CNN to Transformer: A Review of Medical Image Segmentation Models.

Journal of imaging informatics in medicine Mar 4, 2024
Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and treatment. The use of deep learning for image segmentation has become a prevalent trend. The widely ad...
Diagnostic Imaging Humans Neural Networks, Computer Female Liver Image Processing, Computer-Assisted Deep Learning Ovarian Neoplasms
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Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique.

Journal of imaging informatics in medicine Mar 4, 2024
Image segmentation is a crucial task in computer vision and image processing, with numerous segmentation algorithms being found in the literature. It has important applications in scene understanding, medical image analysis, robotic perception, video...
Deep Learning Image Processing, Computer-Assisted Retinal Vessels Neural Networks, Computer Machine Learning Algorithms Humans
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Pan-cancer image segmentation based on feature pyramids and Mask R-CNN framework.

Medical physics Mar 4, 2024
BACKGROUND: Cancer, a disease with a high mortality rate, poses a great threat to patients' physical and mental health and can lead to huge medical costs and emotional damage. With the continuous development of artificial intelligence technologies, d...
Neoplasms Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Echoes of images: multi-loss network for image retrieval in vision transformers.

Medical & biological engineering & computing Mar 4, 2024
This paper introduces a novel approach to enhance content-based image retrieval, validated on two benchmark datasets: ISIC-2017 and ISIC-2018. These datasets comprise skin lesion images that are crucial for innovations in skin cancer diagnosis and tr...
Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Humans Skin Neoplasms Image Processing, Computer-Assisted Databases, Factual
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Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study.

Journal of applied clinical medical physics Mar 4, 2024
PURPOSE: Predicting recurrence following stereotactic body radiotherapy (SBRT) for non-small cell lung cancer provides important information for the feasibility of the individualized radiotherapy and allows to select the appropriate treatment strateg...
Image Processing, Computer-Assisted Lung Neoplasms Carcinoma, Non-Small-Cell Lung Male Middle Aged Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiosurgery Neoplasm Recurrence, Local Radiotherapy Planning, Computer-Assisted Positron Emission Tomography Computed Tomography Retrospective Studies Female Aged, 80 and over Radiomics Aged Machine Learning Humans Algorithms Prognosis
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Pattern classification of interstitial lung diseases from computed tomography images using a ResNet-based network with a split-transform-merge strategy and split attention.

Physical and engineering sciences in medicine Mar 4, 2024
In patients with interstitial lung disease (ILD), accurate pattern assessment from their computed tomography (CT) images could help track lung abnormalities and evaluate treatment efficacy. Based on excellent image classification performance, convolu...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Lung Diseases, Interstitial Algorithms Pattern Recognition, Automated Tomography, X-Ray Computed
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Classification of multi-feature fusion ultrasound images of breast tumor within category 4 using convolutional neural networks.

Medical physics Mar 4, 2024
BACKGROUND: Breast tumor is a fatal threat to the health of women. Ultrasound (US) is a common and economical method for the diagnosis of breast cancer. Breast imaging reporting and data system (BI-RADS) category 4 has the highest false-positive valu...
Image Processing, Computer-Assisted Humans Ultrasonography, Mammary Breast Neoplasms Female Neural Networks, Computer Ultrasonography
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