Výsledky vyhledávání - "Dynamic graph convolutional autoencoder"

Dynamic graph convolutional autoencoder with node-attribute-wise attention for kidney and tumor segmentation from CT volumes

Autoři: Ping Xuan Hui Cui Hongda Zhang a další

Zdroj: Knowledge-Based Systems. 236:107360

Témata: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://www.sciencedirect.com/science/article/pii/S0950705121006225

An adaptive recalibrative contextual squeeze-and-excitation self-attention V-Net for kidney tumor segmentation in RCC imaging.

Autoři: Pabitha, C. Benila, S. Vanathi, B.

Zdroj: European Physical Journal Plus; Aug2025, Vol. 140 Issue 8, p1-22, 22p

Kidney Tumor Segmentation Based on DWR-SegFormer.

Autoři: Deng, Yani Liu, Xin Shao, Lianhe a další

Zdroj: Electronics (2079-9292); Aug2024, Vol. 13 Issue 16, p3226, 17p

Témata: RENAL cell carcinoma, COMPUTED tomography, KIDNEY tumors, RENAL cancer, FEATURE extraction

Mutually enhanced multi-view information learning for segmentation of lung tumor in CT images.

Autoři: Xuan, Ping Xu, Yinfeng Cui, Hui a další

Zdroj: Physics in Medicine & Biology; 4/7/2024, Vol. 69 Issue 7, p1-15, 15p

Témata: LUNG tumors, COMPUTED tomography, LUNGS, EARLY diagnosis

Multi-Scale and Spatial Information Extraction for Kidney Tumor Segmentation: A Contextual Deformable Attention and Edge-Enhanced U-Net.

Autoři: R., Shamija Sherryl R. M. T., Jaya

Zdroj: Journal of Digital Imaging; Feb2024, Vol. 37 Issue 1, p151-166, 16p

Témata: KIDNEY tumors, COMPUTED tomography, ARTIFICIAL intelligence, DESCRIPTIVE statistics, ARTIFICIAL neural networks, DEEP learning, ONE-way analysis of variance, COMPUTER-aided diagnosis, DIGITAL image processing, COMPARATIVE studies, SENSITIVITY & specificity (Statistics), ALGORITHMS

Kidney Cancer Diagnosis and Surgery Selection by Machine Learning from CT Scans Combined with Clinical Metadata.

Autoři: Mahmud, Sakib Abbas, Tariq O. Mushtak, Adam a další

Zdroj: Cancers; Jun2023, Vol. 15 Issue 12, p3189, 25p

Témata: KIDNEY physiology, RENAL cell carcinoma, NEPHRECTOMY, METADATA, RESEARCH methodology, MACHINE learning, ARTIFICIAL intelligence, CONTRAST media, CANCER patients, TUMOR classification, KIDNEY tumors, DESCRIPTIVE statistics, RESEARCH funding, COMPUTED tomography

CMFCUNet: cascaded multi-scale feature calibration UNet for pancreas segmentation.

Autoři: Qiu, Chengjian Song, Yuqing Liu, Zhe a další

Zdroj: Multimedia Systems; Apr2023, Vol. 29 Issue 2, p871-886, 16p

Témata: CALIBRATION, COMPUTED tomography

Korporace: NATIONAL Institutes of Health (U.S.)

Semantic Multiclass Segmentation and Classification of Kidney Lesions.

Autoři: Shamija Sherryl, R. M. R. Jaya, T.

Zdroj: Neural Processing Letters; Apr2023, Vol. 55 Issue 2, p1975-1992, 18p

Témata: CONVOLUTIONAL neural networks, DEEP learning, KIDNEYS, MNEMONICS, IMAGE segmentation, AUTOMATIC classification, IMAGE intensifiers, OVERALL survival

Automatic Segmentation Using Deep Convolutional Neural Networks for Tumor CT Images.

Autoři: Li, Yunbo Li, Xiaofeng

Zdroj: International Journal of Pattern Recognition & Artificial Intelligence; Mar2023, Vol. 37 Issue 3, p1-19, 19p

Témata: CONVOLUTIONAL neural networks, COMPUTED tomography, IMAGE segmentation, FEATURE extraction

Deep Learning with Graph Convolutional Networks: An Overview and Latest Applications in Computational Intelligence.

Autoři: Bhatti, Uzair Aslam Tang, Hao Wu, Guilu a další

Zdroj: International Journal of Intelligent Systems; 2/28/2023, p1-28, 28p

Témata: DEEP learning, COMPUTATIONAL intelligence, NATURAL language processing, ARTIFICIAL intelligence, CONVOLUTIONAL neural networks, MACHINE learning

Multi-Scale and Spatial Information Extraction for Kidney Tumor Segmentation: A Contextual Deformable Attention and Edge-Enhanced U-Net.

Autoři: R SSRM T J

Zdroj: Journal of imaging informatics in medicine [J Imaging Inform Med] 2024 Feb; Vol. 37 (1), pp. 151-166. Date of Electronic Publication: 2024 Jan 12.

Způsob vydávání: Journal Article

Informace o časopise: 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: In Process; MEDLINE