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Retinal vessel segmentation method based on RSP-SA Unet network
Segmenting retinal vessels plays a significant role in the diagnosis of fundus disorders. However, there are two problems in the retinal vessel...
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MD-UNet: a medical image segmentation network based on mixed depthwise convolution
In the process of cancer diagnosis and treatment, accurate extraction of the lesion area helps the doctor to judge the condition. Currently, medical...
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An Approach to Segment Nuclei and Cytoplasm in Lung Cancer Brightfield Images Using Hybrid Swin-Unet Transformer
PurposeSegmentation of nuclei and cytoplasm in cellular images is essential for estimating the prognosis of lung cancer disease. The detection of...
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A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet++
ObjectiveRadiomic and deep learning studies based on magnetic resonance imaging (MRI) of liver tumor are gradually increasing. Manual segmentation of...
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Pulmonary nodule detection based on IR-UNet + +
Lung cancer is one of the cancers with the highest incidence rate and death rate worldwide. An initial lesion of the lung appears as nodules in the...
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Fan beam CT image synthesis from cone beam CT image using nested residual UNet based conditional generative adversarial network
A radiotherapy technique called Image-Guided Radiation Therapy adopts frequent imaging throughout a treatment session. Fan Beam Computed Tomography...
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Re-UNet: a novel multi-scale reverse U-shape network architecture for low-dose CT image reconstruction
AbstractIn recent years, the growing awareness of public health has brought attention to low-dose computed tomography (LDCT) scans. However, the CT...
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Automatic lung tumor segmentation from CT images using improved 3D densely connected UNet
Accurate lung tumor segmentation has great significance in the treatment planning of lung cancer. However, robust lung tumor segmentation becomes...
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BIRGU Net: deformable brain magnetic resonance image registration using gyral-net map and 3D Res-Unet
Deformable image registration is a fundamental procedure in medical imaging. Recently, deep learning-based deformable image registrations have...
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Light-Weight Localization and Scale-Independent Multi-gate UNET Segmentation of Left and Right Ventricles in MRI Images
PurposeHeart segmentation in cardiac magnetic resonance images is heavily used during the assessment of left ventricle global function. Automation of...
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Comparison of deep learning networks for fully automated head and neck tumor delineation on multi-centric PET/CT images
ObjectivesDeep learning-based auto-segmentation of head and neck cancer (HNC) tumors is expected to have better reproducibility than manual...
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Comprehensive evaluation of similarity between synthetic and real CT images for nasopharyngeal carcinoma
BackgroundAlthough magnetic resonance imaging (MRI)-to-computed tomography (CT) synthesis studies based on deep learning have significantly...
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An end-end deep learning framework for lesion segmentation on multi-contrast MR images—an exploratory study in a rat model of traumatic brain injury
Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra—areas of secondary neural injury which are crucial targets for therapeutic...
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Deep Upscale U-Net for automatic tongue segmentation
AbstractIn a treatment or diagnosis related to oral health conditions such as oral cancer and oropharyngeal cancer, an investigation of tongue’s...
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GIFNet: an effective global infection feature network for automatic COVID-19 lung lesions segmentation
AbstractThe ongoing COronaVIrus Disease 2019 (COVID-19) pandemic carried by the SARS-CoV-2 virus spread worldwide in early 2019, bringing about an...
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Segmentation of rectal tumor from multi-parametric MRI images using an attention-based fusion network
Accurate segmentation of rectal tumors is the most crucial task in determining the stage of rectal cancer and develo** suitable therapies. However,...
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PI-RADSAI: introducing a new human-in-the-loop AI model for prostate cancer diagnosis based on MRI
BackgroundThis study aims to develop and validate an artificial intelligence (AI)-aided Prostate Imaging Reporting and Data System (PI-RADS AI ) for...
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Visual Prompting Based Incremental Learning for Semantic Segmentation of Multiplex Immuno-Flourescence Microscopy Imagery
Deep learning approaches are state-of-the-art for semantic segmentation of medical images, but unlike many deep learning applications, medical...
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CAT-Seg: cascaded medical assistive tool integrating residual attention mechanisms and Squeeze-Net for 3D MRI biventricular segmentation
Cardiac image segmentation is a critical step in the early detection of cardiovascular disease. The segmentation of the biventricular is a...
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Connected-UNets: a deep learning architecture for breast mass segmentation
Breast cancer analysis implies that radiologists inspect mammograms to detect suspicious breast lesions and identify mass tumors. Artificial...
