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Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf02980577openalex-snapshot
Beitrag zur Theorie des Ferromagnetismus
inferredcites →https://doi.org/10.1016/1047-3203(90)90014-mopenalex-snapshot
Morphological segmentation
inferredcites →https://doi.org/10.1016/j.imavis.2009.06.017openalex-snapshot
Some links between extremum spanning forests, watersheds and min-cuts
inferredcites →https://doi.org/10.1109/cvpr.1998.698673openalex-snapshot
Markov random fields with efficient approximations
inferredcites →https://doi.org/10.1109/iccv.2001.937505openalex-snapshot
Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images
inferredcites →https://doi.org/10.1109/iccv.2003.1238310openalex-snapshot
Computing geodesics and minimal surfaces via graph cuts
inferredcites →https://doi.org/10.1109/icpr.2006.93openalex-snapshot
A Machine Learning Approach for Locating Boundaries of Liver Tumors in CT Images
inferredcites →https://doi.org/10.1109/iembs.2005.1617181openalex-snapshot
Liver Tumor Volume Estimation By Semi-Automatic Segmentation Method
inferredcites →https://doi.org/10.1109/tpami.1984.4767596openalex-snapshot
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
inferredcites →https://doi.org/10.1109/tpami.2004.60openalex-snapshot
An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision
inferredcites →https://doi.org/10.1117/12.655213openalex-snapshot
Tumor volume measurement and volume measurement comparison plug-ins for VolView using ITK
inferredcites →https://doi.org/10.1201/9781482277234-12openalex-snapshot
The Morphological Approach to Segmentation: The Watershed Transformation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-1-4614-7245-2_5openalex-snapshot
Computational Anatomy in the Abdomen: Automated Multi-Organ and Tumor Analysis from Computed Tomography
inferred← citeshttps://doi.org/10.1007/978-3-030-52791-4_7openalex-snapshot
Segmenting Hepatocellular Carcinoma in Multi-phase CT
inferred← citeshttps://doi.org/10.1007/978-3-642-31196-3_5openalex-snapshot
3D Fuzzy Liver Tumor Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-642-36620-8_20openalex-snapshot
A Cascade Learning Method for Liver Lesion Detection in CT Images
inferred← citeshttps://doi.org/10.1007/978-981-96-6906-6_33openalex-snapshot
Comparative Analysis for the Detection of Cancerous Cells in Liver Organ of Patients Using Marker-Controlled Watershed Transform Segmentation Algorithm Versus Adaptive Region Growing and Graph Cuts
inferred← citeshttps://doi.org/10.1007/s00500-020-05094-1openalex-snapshot
RETRACTED ARTICLE: Automatic segmentation and classification of liver tumor from CT image using feature difference and SVM based classifier-soft computing technique
inferred← citeshttps://doi.org/10.1007/s10462-011-9289-8openalex-snapshot
Performance divergence with data discrepancy: a review
inferred← citeshttps://doi.org/10.1007/s10462-017-9550-xopenalex-snapshot
Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography
inferred← citeshttps://doi.org/10.1007/s11517-016-1495-8openalex-snapshot
Metastatic liver tumour segmentation with a neural network-guided 3D deformable model
inferred← citeshttps://doi.org/10.1007/s11517-018-1803-6openalex-snapshot
Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies
inferred← citeshttps://doi.org/10.1007/s11548-015-1323-xopenalex-snapshot
Improved segmentation of low-contrast lesions using sigmoid edge model
inferred← citeshttps://doi.org/10.1007/s11548-018-1820-9openalex-snapshot
Robust extraction for low-contrast liver tumors using modified adaptive likelihood estimation
inferred← citeshttps://doi.org/10.1007/s11831-023-09901-4openalex-snapshot
Deep Federated Machine Learning-Based Optimization Methods for Liver Tumor Diagnosis: A Review
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2017.02.002openalex-snapshot
An interactive medical image segmentation framework using iterative refinement
inferred← citeshttps://doi.org/10.1016/j.media.2014.04.001openalex-snapshot
Tumor sensitive matching flow: A variational method to detecting and segmenting perihepatic and perisplenic ovarian cancer metastases on contrast-enhanced abdominal CT
inferred← citeshttps://doi.org/10.1016/j.media.2014.10.004openalex-snapshot
Right ventricle segmentation from cardiac MRI: A collation study
inferred← citeshttps://doi.org/10.1038/s41598-017-00746-zopenalex-snapshot
Evaluation of Direct Haptic 4D Volume Rendering of Partially Segmented Data for Liver Puncture Simulation
inferred← citeshttps://doi.org/10.1088/1757-899x/1022/1/012027openalex-snapshot
A comparative study of new and existing segmentation techniques
inferred← citeshttps://doi.org/10.1109/trpms.2021.3059780openalex-snapshot
DefED-Net: Deformable Encoder-Decoder Network for Liver and Liver Tumor Segmentation
inferred← citeshttps://doi.org/10.1117/12.2044049openalex-snapshot
Bladder segmentation in MR images with watershed segmentation and graph cut algorithm
inferred← citeshttps://doi.org/10.1117/12.2217778openalex-snapshot
A general approach to liver lesion segmentation in CT images
inferred← citeshttps://doi.org/10.1117/12.2502810openalex-snapshot
Liver tumor segmentation based on level set
inferred← citeshttps://doi.org/10.1155/2022/4277436openalex-snapshot
AI-DRIVEN Novel Approach for Liver Cancer Screening and Prediction Using Cascaded Fully Convolutional Neural Network
inferred← citeshttps://doi.org/10.2478/msr-2013-0036openalex-snapshot
A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform
inferred← citeshttps://doi.org/10.2478/v10048-012-0023-8openalex-snapshot
Soft-tissues Image Processing: Comparison of Traditional Segmentation Methods with 2D active Contour Methods
inferred← citeshttps://doi.org/10.3389/fmed.2021.653913openalex-snapshot
Accurate Tumor Segmentation via Octave Convolution Neural Network
inferred← citeshttps://doi.org/10.3390/bioengineering10020215openalex-snapshot
Fully Automatic Liver and Tumor Segmentation from CT Image Using an AIM-Unet
inferred← citeshttps://doi.org/10.3390/buildings13081922openalex-snapshot
Ultraviolet Radiation Transmission in Building’s Fenestration: Part II, Exploring Digital Imaging, UV Photography, Image Processing, and Computer Vision Techniques
inferred← citeshttps://doi.org/10.48550/arxiv.1809.05210openalex-snapshot
A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors
inferred← citeshttps://doi.org/10.5897/sre2014.5870openalex-snapshot
Automated classification of coronary artery disease using discrete wavelet transform and back propagation neural network
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