Deep learning techniques for liver and liver tumor segmentation: A review
Liver and liver tumor segmentation from 3D volumetric images has been an active research
area in the medical image processing domain for the last few decades. The existence of …
area in the medical image processing domain for the last few decades. The existence of …
[HTML][HTML] Deep learning for image-based liver analysis—A comprehensive review focusing on malignant lesions
Deep learning-based methods, in particular, convolutional neural networks and fully
convolutional networks are now widely used in the medical image analysis domain. The …
convolutional networks are now widely used in the medical image analysis domain. The …
Automatic liver and lesion segmentation in CT using cascaded fully convolutional neural networks and 3D conditional random fields
Automatic segmentation of the liver and its lesion is an important step towards deriving
quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support …
quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support …
Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks
Automatic segmentation of the liver and hepatic lesions is an important step towards
deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision …
deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision …
Learning normalized inputs for iterative estimation in medical image segmentation
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation
that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual …
that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual …
Ahcnet: An application of attention mechanism and hybrid connection for liver tumor segmentation in ct volumes
H Jiang, T Shi, Z Bai, L Huang - Ieee Access, 2019 - ieeexplore.ieee.org
The liver is a common site for the development of primary (ie, originating from the liver, eg,
hepatocellular carcinoma) or secondary (ie, spread to the liver, eg, colorectal cancer) tumor …
hepatocellular carcinoma) or secondary (ie, spread to the liver, eg, colorectal cancer) tumor …
CT image segmentation of bone for medical additive manufacturing using a convolutional neural network
Background The most tedious and time-consuming task in medical additive manufacturing
(AM) is image segmentation. The aim of the present study was to develop and train a …
(AM) is image segmentation. The aim of the present study was to develop and train a …
Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies
Purpose Radiological longitudinal follow-up of liver tumors in CT scans is the standard of
care for disease progression assessment and for liver tumor therapy. Finding new tumors in …
care for disease progression assessment and for liver tumor therapy. Finding new tumors in …
[HTML][HTML] Comparison of convolutional neural network training strategies for cone-beam CT image segmentation
Background and objective Over the past decade, convolutional neural networks (CNNs)
have revolutionized the field of medical image segmentation. Prompted by the …
have revolutionized the field of medical image segmentation. Prompted by the …
[HTML][HTML] Deep Learning-Based Workflow for Bone Segmentation and 3D Modeling in Cone-Beam CT Orthopedic Imaging
E Tiribilli, L Bocchi - Applied Sciences, 2024 - mdpi.com
In this study, a deep learning-based workflow designed for the segmentation and 3D
modeling of bones in cone beam computed tomography (CBCT) orthopedic imaging is …
modeling of bones in cone beam computed tomography (CBCT) orthopedic imaging is …