Výsledky vyhledávání - Semi-supervised learning 3D medical image segmentation Class imbalance Data augmentation

Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image Segmentation

Autoři: Gu, Yuliang Liu, Yepeng Sun, Zhichao a další

Přispěvatelé: Gu, Yuliang Liu, Yepeng Sun, Zhichao a další

Zdroj: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). :1966-1973

Témata: FOS: Computer and information sciences, Class imbalance, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Semi-supervised learning 3D medical image segmentation Class imbalance Data augmentation, Data augmentation, Computer Vision and Pattern Recognition (cs.CV), Semi-supervised learning, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), 3D medical image segmentation

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2410.14210
https://hal.science/hal-04739628v1

Deep Learning Network with Illuminant Augmentation for Diabetic Retinopathy Segmentation Using Comprehensive Anatomical Context Integration.

Autoři: Chankhachon, Sakon Kansomkeat, Supaporn Bhurayanontachai, Patama a další

Zdroj: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 21, p2762, 32p

Témata: DIABETIC retinopathy, IMAGE segmentation, COMPUTER-assisted image analysis (Medicine), FALSE positive error, DATA augmentation, DEEP learning, TRANSFORMER models, ANATOMICAL variation

ES-UNet: efficient 3D medical image segmentation with enhanced skip connections in 3D UNet.

Autoři: Park, Minyoung Oh, Seungtaek Park, Junyoung a další

Zdroj: BMC Medical Imaging; 8/13/2025, Vol. 25 Issue 1, p1-23, 23p

Témata: DEEP learning, DATA augmentation, FEATURE extraction

Enhancing Highway Scene Understanding: A Novel Data Augmentation Approach for Vehicle-Mounted LiDAR Point Cloud Segmentation.

Autoři: Zhou, Dalong Yi, Yuanyang Wang, Yu a další

Zdroj: Remote Sensing; Jul2025, Vol. 17 Issue 13, p2147, 22p

Témata: DATA augmentation, POINT cloud, SUPERVISED learning, SENSORY perception, INTELLIGENT transportation systems, IMAGE segmentation, TRANSPORTATION corridors

A Hybrid Framework for Red Blood Cell Labeling Using Elliptical Fitting, Autoencoding, and Data Augmentation.

Autoři: Angmanee, Bundasak Wanram, Surasak Thedsakhulwong, Amorn

Zdroj: Journal of Imaging; Sep2025, Vol. 11 Issue 9, p309, 31p

Témata: THALASSEMIA, ANEMIA, CLASSIFICATION algorithms, DATA augmentation, FEATURE extraction, ERYTHROCYTES, HEMATOLOGY

Geografický termín: THAILAND, SOUTHEAST Asia

Tackling class imbalance in computer vision: a contemporary review.

Autoři: Saini, Manisha Susan, Seba

Zdroj: Artificial Intelligence Review; Oct2023 Suppl 1, Vol. 56, p1279-1335, 57p

Témata: DEEP learning, COMPUTER vision, MACHINE learning, TRANSFORMER models, GENERATIVE adversarial networks, ARTIFICIAL vision

Skin Lesion Synthesis and Classification Using an Improved DCGAN Classifier.

Autoři: Behara, Kavita Bhero, Ernest Agee, John Terhile

Zdroj: Diagnostics (2075-4418); Aug2023, Vol. 13 Issue 16, p2635, 29p

Témata: GENERATIVE adversarial networks, DEEP learning, CONVOLUTIONAL neural networks, DATA augmentation, SKIN imaging

Semi‐supervised contextual cognitive augmentation‐based cross‐teaching network for multiclass medical image segmentation.

Autoři: Gai, Di Wu, Yuxuan Xiao, Yusong a další

Zdroj: IET Image Processing (Wiley-Blackwell); 11/13/2024, Vol. 18 Issue 13, p3989-4004, 16p

Témata: DATA mining, DISCRETE cosine transforms, IMAGE processing, IMAGE segmentation, DIAGNOSTIC imaging

Analyzing Overfitting Under Class Imbalance in Neural Networks for Image Segmentation.

Autoři: Li, Zeju Kamnitsas, Konstantinos Glocker, Ben

Zdroj: IEEE Transactions on Medical Imaging; Mar2021, Vol. 40 Issue 3, p1065-1077, 13p

Témata: IMAGE segmentation, PREDICTION models

A review of medical image data augmentation techniques for deep learning applications.

Autoři: Chlap P Min H Vandenberg N a další

Zdroj: Journal of medical imaging and radiation oncology [J Med Imaging Radiat Oncol] 2021 Aug; Vol. 65 (5), pp. 545-563. Date of Electronic Publication: 2021 Jun 19.

Způsob vydávání: Journal Article; Systematic Review

Informace o časopise: Publisher: Wiley-Blackwell Pub. Asia Country of Publication: Australia NLM ID: 101469340 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1754-9485 (Electronic) Linking ISSN: 17549477 NLM ISO Abbreviation: J Med Imaging Radiat Oncol Subsets: MEDLINE

Výrazy ze slovníku MeSH: Deep Learning*, Humans ; Magnetic Resonance Imaging

Medical image segmentation using deep learning: A survey.

Autoři: Wang, Risheng Lei, Tao Cui, Ruixia a další

Zdroj: IET Image Processing (Wiley-Blackwell); Apr2022, Vol. 16 Issue 5, p1243-1267, 25p

Témata: IMAGE segmentation, DEEP learning, DIAGNOSTIC imaging, CONVOLUTIONAL neural networks, THEMATIC analysis

Synergistic medical genetic evolutionary optimization and deep convolutional generative augmentation with SHAP-driven interpretability for precise Alzheimer's disease severity grading.

Autoři: Bharath, H. C. Pradeep, N. Shashidhar, R. a další

Zdroj: Brain Informatics; 11/26/2025, Vol. 12 Issue 1, p1-20, 20p

Témata: ALZHEIMER'S disease, DEEP learning, MEDICAL genetics, DATA quality, DETECTION algorithms, DATA augmentation

Innovative Approach for Diabetic Retinopathy Severity Classification: An AI-Powered Tool using CNN-Transformer Fusion.

Autoři: Rezaee, Khosro Farnami, Fateme

Zdroj: Journal of Biomedical Physics & Engineering; Apr2025, Vol. 15 Issue 2, p137-158, 22p

Témata: CONVOLUTIONAL neural networks, ARTIFICIAL intelligence, DATA augmentation, IMAGE recognition (Computer vision), FUNDUS oculi, DEEP learning

Insights and Considerations in Development and Performance Evaluation of Generative Adversarial Networks (GANs): What Radiologists Need to Know.

Autoři: Yoon, Jeong Taek Lee, Kyung Mi Oh, Jang-Hoon a další

Zdroj: Diagnostics (2075-4418); Aug2024, Vol. 14 Issue 16, p1756, 21p

Témata: GENERATIVE adversarial networks, COMPUTER-assisted image analysis (Medicine), DATA augmentation, ARTIFICIAL intelligence, DEEP learning

Entropy‐guided contrastive learning for semi‐supervised medical image segmentation.

Autoři: Xie, Junsong Wu, Qian Zhu, Renju

Zdroj: IET Image Processing (Wiley-Blackwell); 2/7/2024, Vol. 18 Issue 2, p312-326, 15p

Témata: DIAGNOSTIC imaging, MACHINE learning, IMAGE segmentation, SUPERVISED learning, VIDEO coding, ENTROPY

ROAM: Random layer mixup for semi‐supervised learning in medical images.

Autoři: Bdair, Tariq Wiestler, Benedikt Navab, Nassir a další

Zdroj: IET Image Processing (Wiley-Blackwell); Aug2022, Vol. 16 Issue 10, p2593-2608, 16p

Témata: COMPUTER-assisted image analysis (Medicine), DIAGNOSTIC imaging, INTERPOLATION spaces, IMAGE segmentation, SUPERVISED learning, MACHINE learning

Deep Transfer Learning from Constrained Source to Target Domains in Medical Image Segmentation.

Autoři: Krishnan, Chetana Schmidt, Emma Onuoha, Ezinwanne a další

Zdroj: Journal of Imaging Science & Technology; Nov/Dec2024, Vol. 68 Issue 6, p1-10, 10p

A comparative analysis of different augmentations for brain images.

Autoři: Bajaj S Bala M Angurala M

Zdroj: Medical & biological engineering & computing [Med Biol Eng Comput] 2024 Oct; Vol. 62 (10), pp. 3123-3150. Date of Electronic Publication: 2024 May 24.

Způsob vydávání: Journal Article; Comparative Study

Informace o časopise: Publisher: Springer Country of Publication: United States NLM ID: 7704869 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1741-0444 (Electronic) Linking ISSN: 01400118 NLM ISO Abbreviation: Med Biol Eng Comput Subsets: MEDLINE

Výrazy ze slovníku MeSH: Brain*/diagnostic imaging , Deep Learning* , Tomography, X-Ray Computed*/methods, Humans ; Image Processing, Computer-Assisted/methods ; Algorithms

A NOVEL CARDIAC IMAGE SEGMENTATION METHOD USING AN OPTIMIZED 3D U-NET MODEL.

Autoři: DONG, XUAN MAO, XUETAO YAO, JIAN

Zdroj: Journal of Mechanics in Medicine & Biology; Nov2023, Vol. 23 Issue 9, p1-15, 15p

Témata: IMAGE segmentation, CARDIAC imaging, MEDICAL quality control, COMPUTER-assisted image analysis (Medicine), MEDICAL sciences, IMAGE processing

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

Autoři: Liu Z Kainth K Zhou A a další

Zdroj: NMR in biomedicine [NMR Biomed] 2024 Aug; Vol. 37 (8), pp. e5143. Date of Electronic Publication: 2024 Mar 24.

Způsob vydávání: Journal Article; Review

Informace o časopise: Publisher: Wiley Country of Publication: England NLM ID: 8915233 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1099-1492 (Electronic) Linking ISSN: 09523480 NLM ISO Abbreviation: NMR Biomed Subsets: MEDLINE

Výrazy ze slovníku MeSH: Deep Learning* , Magnetic Resonance Imaging*/methods, Humans ; Image Processing, Computer-Assisted/methods ; Algorithms ; Supervised Machine Learning ; Brain/diagnostic imaging