Search Results - Fully-automated segmentation algorithms*

Fully automated segmentation and classification of renal tumors on CT scans via machine learning

Authors: Jang Hee Han Byung Woo Kim Taek Min Kim et al.

Source: BMC Cancer
BMC Cancer, Vol 25, Iss 1, Pp 1-9 (2025)

Subject Terms: Male, Adult, Radiomics, Research, Angiomyolipoma, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Deep learning, Middle Aged, Renal cell carcinoma, Kidney Neoplasms, Machine Learning, Segmentation, Deep Learning, Machine learning, Humans, Female, Prospective Studies, Tomography, X-Ray Computed, Carcinoma, Renal Cell, RC254-282, Algorithms, CT, Aged

Access URL: https://pubmed.ncbi.nlm.nih.gov/39881216
https://doaj.org/article/cf95ad8a946d41009640b923dcc09928

A concept for fully automated segmentation of bone in ultrasound imaging

Authors: Ananth Hari Ramakrishnan Muthaiah Rajappa Kannan Krithivasan et al.

Source: Sci Rep
Scientific Reports, Vol 15, Iss 1, Pp 1-18 (2025)

Subject Terms: Science, Map of movement, Heel bone, Article, Bone and Bones, Chan–Vese, Image Processing, Computer-Assisted, Medicine, Humans, Segmentation algorithm, Optical-flow, Algorithms, Ultrasonography

Access URL: https://pubmed.ncbi.nlm.nih.gov/40057558
https://doaj.org/article/234d215602524f83889a1a17c3044888

Fully Automated Tooth Segmentation and Labeling for Both Full- and Partial-Arch Intraoral Scans Using Deep Learning.

Authors: Cao L van Nistelrooij N Liu J et al.

Source: International dental journal [Int Dent J] 2025 Oct; Vol. 75 (5), pp. 100950. Date of Electronic Publication: 2025 Aug 14.

Publication Type: Journal Article

Journal Info: Publisher: Elsevier Country of Publication: England NLM ID: 0374714 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1875-595X (Electronic) Linking ISSN: 00206539 NLM ISO Abbreviation: Int Dent J Subsets: MEDLINE

MeSH Terms: Deep Learning* , Tooth*/diagnostic imaging , Image Processing, Computer-Assisted*/methods, Humans ; Algorithms ; Imaging, Three-Dimensional/methods

Information fusion for fully automated segmentation of head and neck tumors from PET and CT images

Authors: Shiri Lord, Isaac Amini, Mehdi Yousefirizi, Fereshteh et al.

Source: Medical Physics. 51:319-333

Subject Terms: fusion, 616.8, 616.0757, PET/CT, Image Processing, segmentation, deep learning, Deep learning, 3. Good health, Segmentation, Head and Neck Neoplasms, Head and Neck Neoplasms/diagnostic imaging, Positron Emission Tomography Computed Tomography, Computer-Assisted/methods, Image Processing, Computer-Assisted, Humans, head and neck cancer, Fusion, Head and neck cancer, Positron Emission Tomography Computed Tomography/methods, Algorithms

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/37475591
https://hdl.handle.net/11370/37a28dd8-d703-48fe-a01d-faf9383815cf
https://research.rug.nl/en/publications/37a28dd8-d703-48fe-a01d-faf9383815cf
https://doi.org/10.1002/mp.16615
https://archive-ouverte.unige.ch/unige:170500
https://doi.org/10.1002/mp.16615
https://portal.findresearcher.sdu.dk/da/publications/50c0ebc9-132e-43e9-aaa7-0bb23f3f160b
https://doi.org/10.1002/mp.16615

Fully Automated Segmentation of Cervical Spinal Cord in Sagittal MR Images Using Swin-Unet Architectures.

Authors: Polattimur, Rukiye Dandıl, Emre Yıldırım, Mehmet Süleyman et al.

Source: Journal of Clinical Medicine; Oct2025, Vol. 14 Issue 19, p6994, 27p

Subject Terms: CERVICAL cord, IMAGE segmentation, TRANSFORMER models, ALGORITHMS, DIAGNOSIS, DEEP learning, MAGNETIC resonance imaging

Fully-automated segmentation of muscle and inter-/intra-muscular fat from magnetic resonance images of calves and thighs: an open-source workflow in Python

Authors: Kenneth Tam Si Wen Liu Sarah Costa et al.

Source: Skelet Muscle
Skeletal Muscle, Vol 14, Iss 1, Pp 1-17 (2024)

Subject Terms: Automated, Male, Aged, 80 and over, Leg, Methodology, Intramuscular fat, Diseases of the musculoskeletal system, Middle Aged, Magnetic Resonance Imaging, Workflow, 03 medical and health sciences, Segmentation, 0302 clinical medicine, RC925-935, Thigh, Adipose Tissue, Image Processing, Computer-Assisted, Humans, Female, Intermuscular fat, Muscle, Skeletal, Muscle adiposity, Algorithms, MRI, Aged

Access URL: https://pubmed.ncbi.nlm.nih.gov/39731189
https://doaj.org/article/b63cf0ebd2c2408b991246773b4e4bc1

A Deep Learning-Based Fully Automated Vertebra Segmentation and Labeling Workflow.

Authors: Lu H Liu M Yu K et al.

Source: British journal of hospital medicine (London, England : 2005) [Br J Hosp Med (Lond)] 2025 Sep 25; Vol. 86 (9), pp. 1-22. Date of Electronic Publication: 2025 Sep 24.

Publication Type: Journal Article

Journal Info: Publisher: MA Healthcare Country of Publication: England NLM ID: 101257109 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1750-8460 (Print) Linking ISSN: 17508460 NLM ISO Abbreviation: Br J Hosp Med (Lond) Subsets: MEDLINE

MeSH Terms: Deep Learning* , Spine*/diagnostic imaging , Spine*/surgery , Spinal Diseases*/surgery , Spinal Diseases*/diagnostic imaging , Surgery, Computer-Assisted*/methods, Humans ; Tomography, X-Ray Computed/methods ; Workflow ; Imaging, Three-Dimensional/methods ; Algorithms

DCE-UNet: a transformer-based fully automated segmentation network for multiple adolescent spinal disorders in x-ray images.

Authors: Xue Z Deng S Yue Y et al.

Source: Biomedical physics & engineering express [Biomed Phys Eng Express] 2025 Sep 01; Vol. 11 (5). Date of Electronic Publication: 2025 Sep 01.

Publication Type: Journal Article

Journal Info: Publisher: IOP Publishing Ltd Country of Publication: England NLM ID: 101675002 Publication Model: Electronic Cited Medium: Internet ISSN: 2057-1976 (Electronic) Linking ISSN: 20571976 NLM ISO Abbreviation: Biomed Phys Eng Express Subsets: MEDLINE

MeSH Terms: Neural Networks, Computer* , Spinal Diseases*/diagnostic imaging , Image Processing, Computer-Assisted*/methods , Radiographic Image Interpretation, Computer-Assisted*/methods, Humans ; Adolescent ; Algorithms

Open-source, fully-automated hybrid cardiac substructure segmentation: development and optimisation

Authors: Robert N. Finnegan Vicky Chin Phillip Chlap et al.

Contributors: Robert N. Finnegan Vicky Chin Phillip Chlap et al.

Source: Phys Eng Sci Med

Subject Terms: cardiotoxicity, Sustainable Development Goals, Scientific Paper, 03 medical and health sciences, Breast cancer, breast cancer, 0302 clinical medicine, Image Processing, Computer-Assisted, Humans, image segmentation, radiotherapy, SDG 3, Retrospective Studies, Image segmentation, Radiotherapy, deep learning, Deep learning, Heart, Cardiotoxicity, 3. Good health, Cardiac substructures, lung cancer, Lung cancer, Tomography, X-Ray Computed, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/36780065

PWD-3DNet: A Deep Learning-Based Fully-Automated Segmentation of Multiple Structures on Temporal Bone CT Scans

Authors: Soodeh Nikan Kylen Van Osch Mandolin Bartling et al.

Source: Electrical and Computer Engineering Publications

Subject Terms: multi-structure, Temporal Bone, fully-automated segmentation, Electrical and Computer Engineering, PWD-3DNet, 03 medical and health sciences, Deep Learning, 0302 clinical medicine, patch-wise, Image Processing, Computer-Assisted, Humans, temporal bone CT, balanced-weighting, Tomography, X-Ray Computed, Temporal bone CT, Biomedical Engineering and Bioengineering, Algorithms

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/33226942
https://ieeexplore.ieee.org/document/9266055
https://pubmed.ncbi.nlm.nih.gov/33226942/
https://dblp.uni-trier.de/db/journals/tip/tip30.html#NikanOBARCAL21
https://ui.adsabs.harvard.edu/abs/2021ITIP...30..739N/abstract
https://www.ncbi.nlm.nih.gov/pubmed/33226942
https://ir.lib.uwo.ca/context/electricalpub/article/1600/viewcontent/SoodehNikan_TIP_finalized_manuscript.pdf

A Fully Automated Method for 3D Individual Tooth Identification and Segmentation in Dental CBCT

Authors: Tae Jun Jang Kang Cheol Kim Hyun Cheol Cho et al.

Source: IEEE Transactions on Pattern Analysis and Machine Intelligence. 44:6562-6568

Subject Terms: FOS: Computer and information sciences, Imaging, Three-Dimensional, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 0202 electrical engineering, electronic engineering, information engineering, Spiral Cone-Beam Computed Tomography, 02 engineering and technology, Cone-Beam Computed Tomography, Tooth, Algorithms

Access URL: https://ieeexplore.ieee.org/ielx7/34/4359286/09445658.pdf
https://pubmed.ncbi.nlm.nih.gov/34077356
http://arxiv.org/abs/2102.06060
https://dblp.uni-trier.de/db/journals/corr/corr2102.html#abs-2102-06060
https://yonsei.pure.elsevier.com/en/publications/a-fully-automated-method-for-3d-individual-tooth-identification-a
https://pubmed.ncbi.nlm.nih.gov/34077356/
https://www.computer.org/csdl/journal/tp/5555/01/09445658/1uaajNYaeQw
https://ieeexplore.ieee.org/document/9445658
https://europepmc.org/article/MED/34077356

Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks

Authors: Julia Krüger Ann-Christin Ostwaldt Lothar Spies et al.

Source: European Radiology. 32:2798-2809

Subject Terms: Artificial intelligence, Multiple Sclerosis, Infratentorial lesions, Magnetic Resonance Imaging, Multiple sclerosis, 03 medical and health sciences, 0302 clinical medicine, MLE@TUHH, Image Processing, Computer-Assisted, Humans, Intra- and inter-rater variability, Lesion segmentation, Neural Networks, Computer, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/34643779
https://www.ncbi.nlm.nih.gov/pubmed/34643779
https://pubmed.ncbi.nlm.nih.gov/34643779/
https://link.springer.com/article/10.1007/s00330-021-08329-3

Fully automated segmentation of brain and scalp blood vessels on multi-parametric magnetic resonance imaging using multi-view cascaded networks.

Authors: Wu S Huang Z Wang M et al.

Source: Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2025 Mar; Vol. 260, pp. 108584. Date of Electronic Publication: 2025 Jan 02.

Publication Type: Journal Article

Journal Info: Publisher: Elsevier Scientific Publishers Country of Publication: Ireland NLM ID: 8506513 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7565 (Electronic) Linking ISSN: 01692607 NLM ISO Abbreviation: Comput Methods Programs Biomed Subsets: MEDLINE

MeSH Terms: Scalp*/blood supply , Scalp*/diagnostic imaging , Brain*/blood supply , Brain*/diagnostic imaging , Magnetic Resonance Imaging*/methods , Blood Vessels*/diagnostic imaging , Image Processing, Computer-Assisted*/methods, Humans ; Deep Learning ; Algorithms ; Neural Networks, Computer ; Automation

Fully-automated multi-organ segmentation tool applicable to both non-contrast and post-contrast abdominal CT: deep learning algorithm developed using dual-energy CT images

Authors: Sun Kyung Jeon Ijin Joo Junghoan Park et al.

Source: Sci Rep
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)

Subject Terms: 03 medical and health sciences, Deep Learning, 0302 clinical medicine, Liver, Science, Abdomen, Medicine, Tomography, X-Ray Computed, Article, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/38388824
https://doaj.org/article/c92f7ce7c6fb4c06ac42c65deb7e104f

Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study.

Authors: Gautam, Ashish Raghav, Prashant Subramaniam, Vijay et al.

Source: Angiology; May2025, Vol. 76 Issue 5, p431-440, 10p

Subject Terms: PREDICTIVE tests, PEARSON correlation (Statistics), DIAGNOSTIC imaging, BLOOD vessels, COMPUTED tomography, CALCINOSIS, RETROSPECTIVE studies, ELECTROCARDIOGRAPHY, DEEP learning, RESEARCH methodology, ARTIFICIAL neural networks, MEDICAL records, ACQUISITION of data, DIGITAL image processing, CORONARY artery disease, AUTOMATION, ALGORITHMS, SENSITIVITY & specificity (Statistics)

Automated abdominal organ segmentation algorithms for non-enhanced CT for volumetry and 3D radiomics analysis

Authors: Park, Junghoan Joo, Ijin Jeon, Sun Kyung et al.

Source: Abdom Radiol (NY)

Subject Terms: Radiography, Abdominal, Male, Adult, Radiomics, Research, Middle Aged, Kidney, Imaging, Three-Dimensional, Liver, Humans, Radiographic Image Interpretation, Computer-Assisted, Feasibility Studies, Female, Radiography, Thoracic, Tomography, X-Ray Computed, Algorithms, Spleen, Aged

Access URL: https://pubmed.ncbi.nlm.nih.gov/39299987

Fully Automated Segmentation of Pulmonary Fibrosis Using Different Software Tools

Authors: Michael Kreuter Hans-Ulrich Kauczor Klaus H. Maier-Hein et al.

Source: Respiration. 100:580-587

Subject Terms: Male, Middle Aged, Models, Biological, Idiopathic Pulmonary Fibrosis, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Case-Control Studies, Linear Models, Humans, Female, Diagnosis, Computer-Assisted, Lung Volume Measurements, Tomography, X-Ray Computed, Lung, Algorithms, Software, Aged

Access URL: https://pubmed.ncbi.nlm.nih.gov/33857945
https://pubmed.ncbi.nlm.nih.gov/33857945/
https://www.ncbi.nlm.nih.gov/pubmed/33857945

Fully Automated Detection of Osteoporosis Stage on Panoramic Radiographs Using YOLOv5 Deep Learning Model and Designing a Graphical User Interface

Authors: Muhammet Üsame ÖZİÇ Melek Tassoker Fatma Yuce

Source: Journal of Medical and Biological Engineering. 43:715-731

Subject Terms: Test data, 0301 basic medicine, Image segmentation, Learning systems, Panoramic radiograph, Graphical user interfaces, Deep learning, Diseases, Panoramic radiographs, Computer operating systems, Decision support systems, Learning algorithms, Learning models, Performance criterion, Automated detection, 03 medical and health sciences, YOLOv5, 0302 clinical medicine, Diagnosis, Automatic detection, Osteoporosis, Deterioration, Fully automated

Fully Automated 3D Vestibular Schwannoma Segmentation with and without Gadolinium-based Contrast Material: A Multicenter, Multivendor Study: a multicenter, multivendor study

Authors: Olaf M. Neve Yunjie Chen Qian Tao et al.

Source: Radiology: Artificial Intelligence. 4

Subject Terms: Skull Base, Machine Learning Algorithms, 03 medical and health sciences, Segmentation, 0302 clinical medicine, Nose, and Throat, Ear, Deep Learning Algorithms, Convolutional Neural Network (CNN), MRI

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/35923375
https://hdl.handle.net/1887/3515774

Ensemble U‐net‐based method for fully automated detection and segmentation of renal masses on computed tomography images

Authors: Schieda Nicola Zabihollahy Fatemeh Krishna Satheesh et al.

Source: Medical Physics. 47:4032-4044

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, Image Processing, Computer-Assisted, Humans, Neural Networks, Computer, Tomography, X-Ray Computed, Algorithms, Kidney Neoplasms

Access URL: https://pubmed.ncbi.nlm.nih.gov/32329074
https://pubmed.ncbi.nlm.nih.gov/32329074/
https://aapm.onlinelibrary.wiley.com/doi/10.1002/mp.14193
https://www.ncbi.nlm.nih.gov/pubmed/32329074