Suchergebnisse - Deep learning architectures and techniques; Segmentation

Enhanced glaucoma detection using U-Net and U-Net plus architectures using deep learning techniques

Autoren: Kumar, B. P. Pradeep Rangaiah, Pramod K.B. Augustine, Robin

Quelle: Wireless Brain-Connect inteRfAce TO machineS: B-CRA TOS, European Union’s Horizon 2020 Research and Innovation Program, Grant agreement ID: 965044 “BOS: Software Principles & Techniques for a Body-centric OS”, the Swedish Foundation for Strategic Research (SSF) grant FUS Photodiagnosis and Photodynamic Therapy. 54

Schlagwörter: Glaucoma, Retinal intra-ocular region, Frame networks, U-NET layers, DRISHTI-GS, DRIONS-DB, HRF

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-567054
https://doi.org/10.1016/j.pdpdt.2025.104621

AI-Based Multi-Organ Segmentation in Gynecologic Laparoscopy: Comparative Evaluation of Deep Learning Architectures for Anatomical Precision and Surgical Applicability.

Autoren: Lee T Lee SH Kim YJ et al.

Quelle: Journal of imaging informatics in medicine [J Imaging Inform Med] 2025 Oct 24. Date of Electronic Publication: 2025 Oct 24.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE

Automatic segmentation of brain structures in magnetic resonance images using deep learning techniques

Autoren: Kushibar, Kaisar

Weitere Verfasser: University/Department: Universitat de Girona. Departament d'Arquitectura i Tecnologia de Computadors

Thesis Advisors: Valverde Valverde, Sergi, Oliver i Malagelada, Arnau, Lladó Bardera, Xavier

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Brain structures, Estructures cerebrals, Estructuras cerebrales, MRI, Magnetic resonance imaging, Imatgeria per ressonància magnètica, Imágenes por resonancia magnética, Deep learning, Aprenentatge profund, Aprendizaje profundo, Subcortical structures, Estructures subcorticals, Estructuras subcorticales, CNN, Convolutional neural network, Xarxa neuronal convolucional, Red neuronal convolucional

Time: 616.8

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/670766

3D point cloud semantic augmentation: Instance segmentation of 360◦ panoramas by deep learning techniques

Autoren: Karara, Ghizlane Hajji, Rafika Poux, Florent

Quelle: Remote Sensing, 13 (18), 3647 (2021-09)

Schlagwörter: 3D point cloud, 3D projection, Deep learning, I point cloud semantics, Instance segmentation, Panoramic image, Semantic augmentation, Convolution neural network, Generalisation, Learning architectures, Learning techniques, Research fields, Segmentation results, Semantic augmentations, Virtual camera, Earth and Planetary Sciences (all), General Earth and Planetary Sciences, Engineering, computing & technology, Computer science, Ingénierie, informatique & technologie, Sciences informatiques

Relation: https://www.mdpi.com/2072-4292/13/18/3647/pdf; urn:issn:2072-4292

Zugangs-URL: https://orbi.uliege.be/handle/2268/291887

Segmentation of malignant lesions on [18F]FDG PET/CT images using deep learning techniques

Autoren: Oliveira, Mafalda Moreira Oliveira, Francisco Paulo Marques de Constantino, Cláudia Santos et al.

Weitere Verfasser: Oliveira, Mafalda Moreira Oliveira, Francisco Paulo Marques de Constantino, Cláudia Santos et al.

Quelle: urn:tid:203254953

Schlagwörter: [18F]FDG PET/CT, Malignant lesions, Deep learning, Fully automatic segmentation, Lesões malignas, Segmentação totalmente automática

Dateibeschreibung: application/pdf

Verfügbarkeit: http://hdl.handle.net/10400.14/40785

Deep learning for retinal vessel segmentation: a systematic review of techniques and applications.

Autoren: Liu, Zhihui Sunar, Mohd Shahrizal Tan, Tian Swee et al.

Quelle: Medical & Biological Engineering & Computing. Aug2025, Vol. 63 Issue 8, p2191-2208. 18p.

Schlagwörter: *TRANSFORMER models, DEEP learning, RETINAL blood vessels, RESEARCH evaluation, GENERATIVE adversarial networks, CONVOLUTIONAL neural networks, EYE inflammation

Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique.

Autoren: Verma PK Kaur J

Quelle: Journal of imaging informatics in medicine [J Imaging Inform Med] 2024 Aug; Vol. 37 (4), pp. 1783-1799. Date of Electronic Publication: 2024 Mar 04.

Publikationsart: Journal Article; Systematic Review

Info zur Zeitschrift: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE

MeSH-Schlagworte: Retinal Vessels*/diagnostic imaging , Deep Learning* , Image Processing, Computer-Assisted*/methods, Humans ; Algorithms ; Machine Learning ; Neural Networks, Computer

Evaluation of Deep Learning Architectures for Complex Immunofluorescence Nuclear Image Segmentation.

Autoren: Kromp F Fischer L Bozsaky E et al.

Quelle: IEEE transactions on medical imaging [IEEE Trans Med Imaging] 2021 Jul; Vol. 40 (7), pp. 1934-1949. Date of Electronic Publication: 2021 Jun 30.

Publikationsart: Journal Article; Research Support, Non-U.S. Gov't

Info zur Zeitschrift: Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 8310780 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1558-254X (Electronic) Linking ISSN: 02780062 NLM ISO Abbreviation: IEEE Trans Med Imaging Subsets: MEDLINE

MeSH-Schlagworte: Deep Learning*, Algorithms ; Fluorescent Antibody Technique ; Image Processing, Computer-Assisted ; Neural Networks, Computer

Implementation of a Deep Learning System for Detection and Classification of Lumpy Skin Disease in Cattle: Enhancing Precision and Efficiency in Veterinary Diagnostics.

Autoren: Pal, Madhumita Behera, Soudamini Mohapatra, Ranjan K. et al.

Quelle: Veterinary Medicine & Science. Nov2025, Vol. 11 Issue 6, p1-20. 20p.

Schlagworte: Lumpy skin disease, Deep learning, Ensemble learning, Veterinary clinical pathology, Health of cattle, Transformer models, Machine learning

Deep Learning Techniques for Lung Cancer Diagnosis with Computed Tomography Imaging: A Systematic Review for Detection, Segmentation, and Classification.

Autoren: Abdullahi, Kabiru Ramakrishnan, Kannan Ali, Aziah Binti

Quelle: Information. Jun2025, Vol. 16 Issue 6, p451. 31p.

Schlagwörter: *Transformer models, *Artificial intelligence, Convolutional neural networks, Computed tomography, Lung cancer, Deep learning

Deep Learning Models for Radiomics-Based Segmentation of Vestibular Schwannoma on Magnetic Resonance Imaging: A Systematic Review and Meta-analysis.

Autoren: Hajikarimloo B Mohammadzadeh I Shirzadi P et al.

Quelle: Journal of imaging informatics in medicine [J Imaging Inform Med] 2025 Nov 17. Date of Electronic Publication: 2025 Nov 17.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE

Deep Learning Segmentation Techniques for Atherosclerotic Plaque on Ultrasound Imaging: A Systematic Review.

Autoren: De Rosa, Laura L'Abbate, Serena Mota da Silva, Eduarda et al.

Quelle: Information. Jun2025, Vol. 16 Issue 6, p491. 25p.

Schlagwörter: *Web databases, Atherosclerotic plaque, Image analysis, Ultrasonic imaging, Science databases

Deep Learning Approaches for Lumbar Spine MRI Segmentation and Classification.

Autoren: Laazab, Kheira Benblidia, Nadjia Baaloul, Ali

Quelle: Traitement du Signal. Jun2025, Vol. 42 Issue 3, p1733-1748. 16p.

Schlagwörter: DEEP learning, IMAGE segmentation, LUMBAR vertebrae, COMPUTER-assisted image analysis (Medicine), COMPUTER-aided diagnosis, CLASSIFICATION, RADIOLOGY, LORDOSIS

High resolution 3D modelling of lumbar spine from MRI using deep learning

Autoren: Ranganathan, Sai Natarajan Thrissur

Weitere Verfasser: University/Department: Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions

Thesis Advisors: Humbert, Ludovic, González Ballester, Miguel Ángel

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Spine modelling, Deep learning, Feature fusion, Differentiable rendering, Domain adaptation, Biomechanical simulation, Modelatge de la columna vertebral, Aprenentatge profund, Fusió de característiques, Representació diferenciable, Adaptació del domini, Simulació biomecànica

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/692569

Deep-learning-based automatic liver segmentation using computed tomography images in dogs.

Autoren: Lee, Seungyeon Shimbo, Genya Yokoyama, Nozomu et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-10. 10p.

Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning

Autoren: Bustamante, Mariana Viola, Federica Engvall, Jan et al.

Quelle: Journal of Magnetic Resonance Imaging. 57(1):191-203

Schlagwörter: cardiovascular MRI, 4D flow MRI, segmentation, deep learning, convolutional neural networks

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-184998
https://doi.org/10.1002/jmri.28221

Augmented histopathology: Enhancing colon cancer detection through deep learning and ensemble techniques.

Autoren: Gowthamy J Ramesh SSS

Quelle: Microscopy research and technique [Microsc Res Tech] 2025 Jan; Vol. 88 (1), pp. 298-314. Date of Electronic Publication: 2024 Sep 30.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Wiley-Liss Country of Publication: United States NLM ID: 9203012 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0029 (Electronic) Linking ISSN: 1059910X NLM ISO Abbreviation: Microsc Res Tech Subsets: MEDLINE

MeSH-Schlagworte: Deep Learning* , Colonic Neoplasms*/pathology , Colonic Neoplasms*/diagnosis , Image Processing, Computer-Assisted*/methods, Humans ; Neural Networks, Computer ; Algorithms

Lung Nodule Segmentation and Classification using Image Processing and Deep Learning Techniques.

Autoren: Anjum, Hiba Sasidhar, B. Rajesh, T.

Quelle: Grenze International Journal of Engineering & Technology (GIJET); Jan2025, Vol. 11 Issue Part2, p2838-2845, 8p

Schlagwörter: CONVOLUTIONAL neural networks, IMAGE recognition (Computer vision), LUNG cancer, IMAGE processing, PULMONARY nodules

Advancing Pulmonary Embolism Detection with Integrated Deep Learning Architectures.

Autoren: Biret CB Gurbuz S Akbal E et al.

Quelle: Journal of imaging informatics in medicine [J Imaging Inform Med] 2025 Apr 25. Date of Electronic Publication: 2025 Apr 25.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE

An Efficient Deep Learning Based AgriResUpNet Architecture for Semantic Segmentation of Crop and Weed Images.

Autoren: Hussain, Ali Asgar Nair, Pramod Sekharan

Quelle: Ingénierie des Systèmes d'Information. Oct2024, Vol. 29 Issue 5, p1829-1845. 17p.

Schlagwörter: WEED control, AGRICULTURE, CROPS, GROWING season, SYSTEM identification, DEEP learning