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Predicting Cervical Cancer Outcomes: Statistics, Images, and Machine Learning
Frontiers in Artificial Intelligence, 2021 Cervical cancer is a very common and severe disease in women worldwide. Accurate prediction of its clinical outcomes will help adjust or optimize the treatment of cervical cancer and benefit the patients.
Wei Luo
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H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation [PDF]
NeurocomputingIn the field of medical image segmentation, variant models based on Convolutional Neural Networks (CNNs) and Visual Transformers (ViTs) as the base modules have been very widely developed and applied.
Renkai Wu +3 more
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Deep Convolutional Neural Networks in Medical Image Analysis: A Review
Inf.Deep convolutional neural networks (CNNs) have revolutionized medical image analysis by enabling the automated learning of hierarchical features from complex medical imaging datasets.
Ibomoiye Domor Mienye +4 more
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Medical Image Segmentation: A Comprehensive Review of Deep Learning-Based Methods
TomographyMedical image segmentation is a critical application of computer vision in the analysis of medical images. Its primary objective is to isolate regions of interest in medical images from the background, thereby assisting clinicians in accurately ...
Yuxiao Gao +5 more
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Regression to Classification: Ordinal Prediction of Calcified Vessels Using Customized ResNet50
IEEE Access, 2023 A substantial percentage of women die from cardiovascular disease (CVD). Computed tomography (CT) scan helps predict/monitor CVD-related diseases. However, previous studies found relation to assessing the risk of CVD by estimating severity of breast ...
Hosna Asma-Ull, Il Dong Yun, Bo La Yun
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Applied Sciences, 2020 Malignant lesions are a huge threat to human health and have a high mortality rate. Locating the contour of organs is a preparation step, and it helps doctors diagnose correctly.
Chen Li, Wei Chen, Yusong Tan
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Deep Learning Applications in Medical Image Processing
Acta Infologica, 2021 Medical imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), mammography, ultrasound and x-ray have been used for the diagnosis and treatment of diseases for many years.
Ayşe Gül Eker, Nevcihan Duru
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European Radiology ExperimentalObjective Primary sclerosing cholangitis (PSC) is a rare fibroinflammatory hepatobiliary disease with a highly variable clinical course. Identifying patients at risk for poor outcomes remains challenging. Magnetic resonance imaging (MRI)-based approaches
Wolf C. Bartholomä +7 more
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A New Deep-Learning-Based Model for Breast Cancer Diagnosis from Medical Images
Diagnostics, 2023 Breast cancer is one of the most prevalent cancers among women worldwide, and early detection of the disease can be lifesaving. Detecting breast cancer early allows for treatment to begin faster, increasing the chances of a successful outcome.
Salman Zakareya +2 more
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Scientific ReportsMedical Object Detection (MOD) is a clinically relevant image processing method that locates structures of interest in radiological image data at object-level using bounding boxes.
Gabriel Rashidi +5 more
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