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Constantly optimized mean teacher for semi-supervised 3D MRI image segmentation
AbstractThe mean teacher model and its variants, as important methods in semi-supervised learning, have demonstrated promising performance in...
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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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Automatic segmentation of brain glioma based on XY-Net
Glioma is a malignant primary brain tumor, which can easily lead to death if it is not detected in time. Magnetic resonance imaging is the most...
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Accurate object localization facilitates automatic esophagus segmentation in deep learning
BackgroundCurrently, automatic esophagus segmentation remains a challenging task due to its small size, low contrast, and large shape variation. We...
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Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation
Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on...
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Phytoplankton Image Segmentation and Annotation Method Based on Microscopic Fluorescence
Microscopic phytoplankton segmentation is an important part of water quality assessment. The segmentation of microscopic phytoplankton still faces...
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mResU-Net: multi-scale residual U-Net-based brain tumor segmentation from multimodal MRI
Brain tumor segmentation is an important direction in medical image processing, and its main goal is to accurately mark the tumor part in brain MRI....
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MSNSegNet: attention-based multi-shape nuclei instance segmentation in histopathology images
AbstractIn clinical research, the segmentation of irregularly shaped nuclei, particularly in mesenchymal areas like fibroblasts, is crucial yet often...
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LMU-Net: lightweight U-shaped network for medical image segmentation
AbstractDeep learning technology has been employed for precise medical image segmentation in recent years. However, due to the limited available...
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Dual encoder network with transformer-CNN for multi-organ segmentation
Medical image segmentation is a critical step in many imaging applications. Automatic segmentation has gained extensive concern using a convolutional...
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Unsupervised deep consistency learning adaptation network for cardiac cross-modality structural segmentation
AbstractDeep neural networks have recently been succeessful in the field of medical image segmentation; however, they are typically subject to...
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An artificial intelligence model for the semantic segmentation of neoplasms on images of the skin
We present here an artificial intelligence model based on deep learning for semantic segmentation of dermatoscopic images of skin neoplasms. The...
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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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Deep convolutional neural network for hippocampus segmentation with boundary region refinement
Accurately segmenting the hippocampus from magnetic resonance (MR) brain images is a crucial step in studying brain disorders. However, this task is...
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SCAN: sequence-based context-aware association network for hepatic vessel segmentation
Accurate segmentation of hepatic vessel is significant for the surgeons to design the preoperative planning of liver surgery. In this paper, a...
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A Review of Brain Tumor Segmentation Using MRIs from 2019 to 2023 (Statistical Information, Key Achievements, and Limitations)
PurposeA brain tumor is defined as any group of atypical cells occupying space in the brain. There are more than 120 types of them. MRI scans are...
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A panoptic segmentation dataset and deep-learning approach for explainable scoring of tumor-infiltrating lymphocytes
Tumor-Infiltrating Lymphocytes (TILs) have strong prognostic and predictive value in breast cancer, but their visual assessment is subjective. To...
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HPFG: semi-supervised medical image segmentation framework based on hybrid pseudo-label and feature-guiding
Semi-supervised learning methods have been attracting much attention in medical image segmentation due to the lack of high-quality annotation. To...
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A multi-task deep learning model for EGFR genoty** prediction and GTV segmentation of brain metastasis
BackgroundThe precise prediction of epidermal growth factor receptor (EGFR) mutation status and gross tumor volume (GTV) segmentation are crucial...
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A spine segmentation method based on scene aware fusion network
BackgroundIntervertebral disc herniation, degenerative lumbar spinal stenosis, and other lumbar spine diseases can occur across most age groups. MRI...
