[1]
|
LiM-Net: Lightweight multi-level multiscale network with deep residual learning for automatic liver segmentation in CT images
|
|
Biomedical Signal Processing and …,
2023 |
|
|
[2]
|
M2UNet++: A modified multi-scale UNet++ architecture for automatic liver segmentation from computed tomography images
|
|
Research Anthology on Improving …,
2023 |
|
|
[3]
|
MFCA-Net: Multiscale feature fusion with channel-wise attention network for automatic liver segmentation from CT images
|
|
… Conference on Computer Vision and Image …,
2022 |
|
|
[4]
|
Multi-organ Segmentation Network with Adversarial Performance Validator
|
|
arXiv preprint arXiv:2204.07850,
2022 |
|
|
[5]
|
RMS-UNet: Residual multi-scale UNet for liver and lesion segmentation
|
|
Artificial Intelligence in Medicine,
2022 |
|
|
[6]
|
HFRU-Net: High-level feature fusion and recalibration unet for automatic liver and tumor segmentation in CT images
|
|
Computer Methods and Programs in …,
2022 |
|
|
[7]
|
Soft optimization techniques for automatic liver cancer detection in abdominal liver images
|
|
… journal of health …,
2022 |
|
|
[8]
|
Deep learning for automated normal liver volume estimation
|
|
Radiology,
2022 |
|
|
[9]
|
A Deep Learning Approach for Liver and Tumor Segmentation in CT Images Using ResUNet
|
|
Bioengineering,
2022 |
|
|
[10]
|
Liver Tumor Localization Based on YOLOv3 and 3D-Semantic Segmentation Using Deep Neural Networks
|
|
Diagnostics,
2022 |
|
|
[11]
|
Modified U-Net for fully automatic liver segmentation from abdominal CT-image
|
|
International …,
2022 |
|
|
[12]
|
DMSAN: Deep Multi‐Scale Attention Network for Automatic Liver Segmentation From Abdomen CT Images
|
|
Medical Imaging and Health …,
2022 |
|
|
[13]
|
Quantification of Liver-Lung Shunt Fraction on 3D SPECT/CT Images for Selective Internal Radiation Therapy of Liver Cancer Using CNN-Based Segmentations and …
|
|
CT Images for …,
2022 |
|
|
[14]
|
Symmetric Reconstruction of Functional Liver Segments and Cross-Individual Correspondence of Hepatectomy. Diagnostics 2021, 11, 852
|
|
2021 |
|
|
[15]
|
TPCNN: Two-path convolutional neural network for tumor and liver segmentation in CT images using a novel encoding approach
|
|
2021 |
|
|
[16]
|
MS-UNet: A multi-scale UNet with feature recalibration approach for automatic liver and tumor segmentation in CT images
|
|
2021 |
|
|
[17]
|
Semi-automatic liver segmentation based on probabilistic models and anatomical constraints
|
|
2021 |
|
|
[18]
|
Numerical Evaluation on Parametric Choices Influencing Segmentation Results in Radiology Images—A Multi-Dataset Study
|
|
2021 |
|
|
[19]
|
Symmetric Reconstruction of Functional Liver Segments and Cross-Individual Correspondence of Hepatectomy
|
|
2021 |
|
|
[20]
|
Cascaded SE-ResUnet for Segmentation of Thoracic Organs at Risk
|
|
Neurocomputing,
2021 |
|
|
[21]
|
Accurate Liver segmentation using 3D CNNs with high level shape constraints
|
|
2020 |
|
|
[22]
|
Some Studies on Automatic Liver Segmentation
|
|
2020 |
|
|
[23]
|
A workflow for automated segmentation of the liver surface, hepatic vasculature and biliary tree anatomy from multiphase MR images
|
|
2020 |
|
|
[24]
|
Automatic Extraction of Lesions and Hepatic Structures in Liver using Segmentation Techniques
|
|
2020 |
|
|
[25]
|
Uncertainty-aware Domain Alignment for Anatomical Structure Segmentation
|
|
2020 |
|
|
[26]
|
Multi-stage Threshold Method for Liver Tumor Segmentation in CT scan Images and its Implementation for FPGA
|
|
2020 |
|
|
[27]
|
基于卷积神经网络和超像素的 CT 图像肝脏分割
|
|
2020 |
|
|
[28]
|
BATCH NORMALIZED CONVOLUTION NEURAL NETWORK FOR LIVER SEGMENTATION
|
|
Signal & Image Processing: An International Journal,
2020 |
|
|
[29]
|
Liver Segemtation in CT Image with No-edge-cuting UNet
|
|
2020 |
|
|
[30]
|
Exploring new numerical methods for the simulation of soft tissue deformations in surgery assistance
|
|
2020 |
|
|
[31]
|
Компьютерная томография в планировании хирургического лечения больных с альвеококкозом печени
|
|
2020 |
|
|
[32]
|
3-D Liver reconstruction and modeling for surgical simulation
|
|
2020 |
|
|
[33]
|
Liver Extraction Using Residual Convolution Neural Networks From Low-Dose CT Images.
|
|
2019 |
|
|
[34]
|
Федеральное государственное бюджетное учреждение ?Государственный научный центр Российской Федерации-Федеральный медицинский биофизический центр им. АИ Бурназяна? Федерального медико-биологического агентства России
|
|
2019 |
|
|
[35]
|
Liver Extraction Using Residual Convolution Neural Networks From Low-Dose CT Images
|
|
2019 |
|
|
[36]
|
Automatic segmentation and determining radiodensity of the liver in a large-scale CT database
|
|
2019 |
|
|
[37]
|
Survey on liver tumour resection planning system: steps, techniques, and parameters
|
|
2019 |
|
|
[38]
|
Automatic liver tumour segmentation in CT combining FCN and NMF-based deformable model
|
|
2019 |
|
|
[39]
|
A Novel Automatic Liver Segmentation by Level Set Method Over Real-Time Sensory Computed Tomography
|
|
2019 |
|
|
[40]
|
A fully automatic computer-aided diagnosis system for hepatocellular carcinoma using convolutional neural networks
|
|
2019 |
|
|
[41]
|
Evaluating porosity estimates for sandstones based on X-ray micro-tomographic images
|
|
Solid Earth Discuss.,
2019 |
|
|
[42]
|
A Novel Amalgamated Liver Tumor Prediction Technique (ALTP)
|
|
2018 |
|
|
[43]
|
POLYSULFIDE MITIGATION AT THE
|
|
2018 |
|
|
[44]
|
Automatic liver segmentation from ct scans using intensity analysis and level-set active contours
|
|
2018 |
|
|
[45]
|
A novel CT to cone-beam CT registration method enables immediate real-time intraprocedural three-dimensional assessment of ablative treatments of liver …
|
|
CardioVascular and Interventional Radiology,
2018 |
|
|
[46]
|
3D Convolutional Neural Network for Liver Tumor Segmentation
|
|
Dissertation, Open Repository of the University of Porto,
2018 |
|
|
[47]
|
Geometric and Topological Modelling of Organs and Vascular Structures from CT Data
|
|
2018 |
|
|
[48]
|
Evaluation of porositiy and permeability estimates for rock samples based on X-ray micro-tomography
|
|
2018 |
|
|
[49]
|
Liver segmentation using 3D CT scans.
|
|
2018 |
|
|
[50]
|
Automatic Liver and Tumor Segmentation from CT Scan Images using Gabor Feature and Machine Learning Algorithms
|
|
2018 |
|
|
[51]
|
Automatic Organ Segmentation for CT Scans Based on Super-Pixel and Convolutional Neural Networks
|
|
Journal of Digital Imaging,
2018 |
|
|
[52]
|
Spleen segmentation in MRI sequence images using template matching and active contours
|
|
Procedia Computer Science,
2018 |
|
|
[53]
|
Liver segmentation: A survey of the state-of-the-art
|
|
2017 |
|
|
[54]
|
Patient‐specific quantification of image quality: an automated technique for measuring the distribution of organ Hounsfield units in clinical chest CT images
|
|
Medical physics,
2017 |
|
|
[55]
|
A Novel Level Set Segmentation Algorithm for Computer-Aided Hepatic Surgical Planning
|
|
2017 |
|
|
[56]
|
Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies
|
|
International Journal of Computer Assisted Radiology and Surgery,
2017 |
|
|
[57]
|
Define Interior Structure for Better Liver Segmentation Based on CT Images
|
|
Computer Vision,
2017 |
|
|
[58]
|
Level Set Based Liver Segmentation and Classification by SVM
|
|
Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications,
2017 |
|
|
[59]
|
Atlas based 3D liver segmentation using adaptive thresholding and superpixel approaches
|
|
2017 |
|
|
[60]
|
An Adaptive Method for Fully Automatic Liver Segmentation in Medical MRI-Images
|
|
International Journal of Computer Applications,
2017 |
|
|
[61]
|
Segmentation of Spleen with Pathology from abdominal MRI
|
|
2017 |
|
|
[62]
|
3D liver segmentation from abdominal computed tomography scans based on a novel level set model
|
|
2017 |
|
|
[63]
|
Simulation of Pixel wise temperature prediction for Liver Tumor by High Intensity Focused Ultrasound Ablations
|
|
2017 |
|
|
[64]
|
Segmentation of Liver Organ using Marker Watershed Transform Algorithm for CT Scan Images
|
|
2016 International Conference on Communication and Signal Processing (ICCSP),
2016 |
|
|
[65]
|
Knowledge-Based System Guided Automatic Contour Segmentation of Abdominal Structures in CT Scans
|
|
2016 |
|
|
[66]
|
Liver segmentation using location and intensity probabilistic atlases
|
|
2016 |
|
|
[67]
|
Machine learning-based lung nodule detection on chest x-ray radiographs
|
|
2016 |
|
|
[68]
|
Experiments with automatic segmentation of liver parenchyma using texture description
|
|
Pattern Recognition and Image Analysis,
2016 |
|
|
[69]
|
Computational Model of Pixel Wise Temperature Prediction for Liver Tumor by High Intensity Focused Ultrasound Ablations
|
|
Information Systems Design and Intelligent Applications,
2016 |
|
|
[70]
|
Full‐Automated Liver Segmentation Using Sobolev Gradient Based Level Set Evolution
|
|
International journal for numerical methods in biomedical engineering,
2016 |
|
|
[71]
|
Accuracy of simple approaches to assessing liver volume in radiological imaging
|
|
Abdominal Radiology,
2016 |
|
|
[72]
|
Genauigkeit von einfachen Ansätzen zur Abschätzung des Lebervolumens mit bildgebenden Verfahren
|
|
2016 |
|
|
[73]
|
Desarrollo de algoritmos de procesamiento de imagen avanzado para interpretación de imágenes médicas. Aplicación a segmentación de hígado sobre imágenes de Resonancia Magnética multisecuencia
|
|
Thesis,
2016 |
|
|
[74]
|
An Overview of Machine Learning in Medical Image Analysis: Trends in Health Informatics
|
|
Classification and Clustering in Biomedical Signal Processing,
2016 |
|
|
[75]
|
Automatic Liver Segmentation on Volumetric CT Images Using Supervoxel-Based Graph Cuts
|
|
Computational and mathematical methods in medicine,
2016 |
|
|
[76]
|
Fully automated liver segmentation using Sobolev gradient‐based level set evolution
|
|
International journal for numerical methods in biomedical engineering,
2016 |
|
|
[77]
|
Implementation of K-means segmentation algorithm on Intel Xeon Phi and GPU: Application in medical imaging
|
|
Advances in Engineering Software,
2016 |
|
|
[78]
|
Investigating the Effectiveness of Wavelet Approximations in Resizing Images for Ultrasound Image Classification
|
|
Journal of Medical Systems,
2016 |
|
|
[79]
|
Automated Liver Tumor Detection Using Markov Random Field Segmentation
|
|
Procedia Technology,
2016 |
|
|
[80]
|
Tumor Segmentation and Automated Training for Liver Cancer Isolation
|
|
2016 |
|
|
[81]
|
Segmentation of liver using marker watershed transform algorithm for CT scan images
|
|
2016 |
|
|
[82]
|
Active Contour with Contrast Enhancement for Automatic Liver and Tumor Segmentation
|
|
Journal of Medical Imaging and Health Informatics,
2016 |
|
|
[83]
|
A Brief Survey of Spleen Segmentation in MRI and CT Images
|
|
2016 |
|
|
[84]
|
Desarrollo de algoritmos de procesamiento de imagen avanzado para interpretación de imágenes médicas. Aplicación a segmentación de hígado sobre imágenes …
|
|
2016 |
|
|
[85]
|
Review of the Software Used for 3D Volumetric Reconstruction of the Liver
|
|
International Journal of Computer and Information Engineering,
2015 |
|
|
[86]
|
AModified DISTANCE REGULARIZED LEVEL SET MODEL FOR LIVER SEGMENTATION FROM CT IMAGES
|
|
2015 |
|
|
[87]
|
Studying methods of automatic liver segmentation from MRI images
|
|
2015 |
|
|
[88]
|
Learning Based Random Walks for Automatic Liver Segmentation in CT Image
|
|
Advances in Image and Graphics Technologies,
2015 |
|
|
[89]
|
Liver Tumor Detection using Artificial Neural Networks for Medical Images
|
|
International Journal for Innovative Research in Science and Technology,
2015 |
|
|
[90]
|
A Study of Effective Segmentation Techniques for Liver Segmentation
|
|
International Journal of Advanced Research in Computer Engineering & Technology,
2015 |
|
|
[91]
|
3D Liver Segmentation from CT Images Using a Level Set Method Based on a Shape and Intensity Distribution Prior
|
|
International Journal of Computer and Information Engineering,
2015 |
|
|
[92]
|
结合先验稀疏字典和空洞填充的 CT 图像肝脏分割
|
|
光学精密工程,
2015 |
|
|
[93]
|
A MODIFIED DISTANCE REGULARIZED LEVEL SET MODEL FOR LIVER SEGMENTATION FROM CT IMAGES
|
|
Signal & Image Processing,
2015 |
|
|
[94]
|
Smoothed shock filtered defuzzification with Zernike moments for liver tumor extraction in MR images
|
|
Image Processing Theory, Tools and Applications (IPTA), 2015 International Conference on,
2015 |
|
|
[95]
|
Automatic volumetric localization of the liver in abdominal CT scans using low level processing and shape priors
|
|
2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA),
2015 |
|
|
[96]
|
Advanced image processing methods for automatic liver segmentation
|
|
2015 |
|
|
[97]
|
Accurate object segmentation using novel active shape and appearance models based on support vector machine learning
|
|
Audio, Language and Image Processing (ICALIP), 2014 International Conference on,
2014 |
|
|
[98]
|
Robust blood vessel surface reconstruction for interactive simulations from patient data
|
|
Thèse,
2014 |
|
|
[99]
|
Robust blood vessel reconstruction for interactive medical simulations
|
|
Medical Imaging. Université des Sciences et Technologie de Lille - Lille I,
2014 |
|
|
[100]
|
Review methods for image segmentation from computed tomography images
|
|
AIP Conference Proceedings,
2014 |
|
|
[101]
|
A ROBUST CT SCAN APPLICATION FOR PRIOR STAGE LIVER DISORDER PREDICTION WITH GOOGLENET DEEPLEARNING TECHNIQUE
|
|
2006 |
|
|
[102]
|
Cascaded Network for Segmenting Liver Tumors Considering Information Extraction and Refinement
|
|
|
|
|
[103]
|
Wavelet Transform Based Volumetric Deep Learning Liver Segmentation
|
|
|
|
|