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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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Aorta Segmentation in 3D CT Images by Combining Image Processing and Machine Learning Techniques
PurposeAorta segmentation is extremely useful in clinical practice, allowing the diagnosis of numerous pathologies, such as dissections, aneurysms...
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Multi-organ landscape of therapy-resistant melanoma
Metastasis and failure of present-day therapies represent the most common causes of mortality in patients with cutaneous melanoma. To identify the...
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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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Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 map**
Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms...
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Image Segmentation in 3D Brachytherapy Using Convolutional LSTM
PurposeThe accuracy of the segmentation of the target lesion and at-risk surrounding organs is important for cervical cancer patients treated with...
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Segmentation of liver and liver lesions using deep learning
Segmentation of organs and lesions could be employed for the express purpose of dosimetry in nuclear medicine, assisted image interpretations, and...
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ThoraxNet: a 3D U-Net based two-stage framework for OAR segmentation on thoracic CT images
An important phase of radiation treatment planning is the accurate contouring of the organs at risk (OAR), which is necessary for the dose...
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A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy
PurposeFast and accurate outlining of the organs at risk (OARs) and high-risk clinical tumor volume (HRCTV) is especially important in high-dose-rate...
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Advanced 3D Visualization and 3D Printing in Radiology
Since the discovery of X-rays in 1895, medical imaging systems have played a crucial role in medicine by permitting the visualization of internal...
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Context fusion network with multi-scale-aware skip connection and twin-split attention for liver tumor segmentation
AbstractManually annotating liver tumor contours is a time-consuming and labor-intensive task for clinicians. Therefore, automated segmentation is...
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Parotid Gland Segmentation Using Purely Transformer-Based U-Shaped Network and Multimodal MRI
Parotid gland tumors account for approximately 2% to 10% of head and neck tumors. Segmentation of parotid glands and tumors on magnetic resonance...
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An Introductory Module in Medical Image Segmentation for BME Students
To support recent trends toward the use of patient-specific anatomical models from medical imaging data, we present a learning module for use in the...
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Sparse deep belief network coupled with extended local fuzzy active contour model-based liver cancer segmentation from abdomen CT images
Liver cancer from abdominal CT images must be accurately segmented for the purpose of diagnosis with treatment planning. But, the similarity in gray...
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VascuConNet: an enhanced connectivity network for vascular segmentation
Medical image segmentation commonly involves diverse tissue types and structures, including tasks such as blood vessel segmentation and nerve fiber...
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Segmentation and Volumetric Analysis of Heart from Cardiac CT Images
PurposeCardiac CT is a valuable diagnostic tool in evaluating cardiovascular diseases. Accurate segmentation of the heart and its structures from...
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Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis
BackgroundThis paper attempts to conduct a systematic review and meta-analysis of deep learning (DLs) models for cervical cancer CT image...
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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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ResDAC-Net: a novel pancreas segmentation model utilizing residual double asymmetric spatial kernels
The pancreas not only is situated in a complex abdominal background but is also surrounded by other abdominal organs and adipose tissue, resulting in...
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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...
