175 related articles for article (PubMed ID: 36322109)
1. Automatic Screening of Pediatric Renal Ultrasound Abnormalities: Deep Learning and Transfer Learning Approach.
Tsai MC; Lu HH; Chang YC; Huang YC; Fu LS
JMIR Med Inform; 2022 Nov; 10(11):e40878. PubMed ID: 36322109
[TBL] [Abstract][Full Text] [Related]
2. Computer-aided diagnosis of congenital abnormalities of the kidney and urinary tract in children based on ultrasound imaging data by integrating texture image features and deep transfer learning image features.
Zheng Q; Furth SL; Tasian GE; Fan Y
J Pediatr Urol; 2019 Feb; 15(1):75.e1-75.e7. PubMed ID: 30473474
[TBL] [Abstract][Full Text] [Related]
3. The application of artificial intelligence to support biliary atresia screening by ultrasound images: A study based on deep learning models.
Hsu FR; Dai ST; Chou CM; Huang SY
PLoS One; 2022; 17(10):e0276278. PubMed ID: 36260613
[TBL] [Abstract][Full Text] [Related]
4. Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal.
Xie HN; Wang N; He M; Zhang LH; Cai HM; Xian JB; Lin MF; Zheng J; Yang YZ
Ultrasound Obstet Gynecol; 2020 Oct; 56(4):579-587. PubMed ID: 31909548
[TBL] [Abstract][Full Text] [Related]
5. Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation.
Lee H; Hong H; Kim J; Jung DC
Med Phys; 2018 Apr; 45(4):1550-1561. PubMed ID: 29474742
[TBL] [Abstract][Full Text] [Related]
6. Automated semantic labeling of pediatric musculoskeletal radiographs using deep learning.
Yi PH; Kim TK; Wei J; Shin J; Hui FK; Sair HI; Hager GD; Fritz J
Pediatr Radiol; 2019 Jul; 49(8):1066-1070. PubMed ID: 31041454
[TBL] [Abstract][Full Text] [Related]
7. Computer-aided diagnostic system based on deep learning for classifying colposcopy images.
Liu L; Wang Y; Liu X; Han S; Jia L; Meng L; Yang Z; Chen W; Zhang Y; Qiao X
Ann Transl Med; 2021 Jul; 9(13):1045. PubMed ID: 34422957
[TBL] [Abstract][Full Text] [Related]
8. An ensemble of deep neural networks for kidney ultrasound image classification.
Sudharson S; Kokil P
Comput Methods Programs Biomed; 2020 Dec; 197():105709. PubMed ID: 32889406
[TBL] [Abstract][Full Text] [Related]
9. Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making.
Ciritsis A; Rossi C; Eberhard M; Marcon M; Becker AS; Boss A
Eur Radiol; 2019 Oct; 29(10):5458-5468. PubMed ID: 30927100
[TBL] [Abstract][Full Text] [Related]
10. A computer-aided diagnostic framework for coronavirus diagnosis using texture-based radiomics images.
Attallah O
Digit Health; 2022; 8():20552076221092543. PubMed ID: 35433024
[TBL] [Abstract][Full Text] [Related]
11. Automated detection of leukemia by pretrained deep neural networks and transfer learning: A comparison.
Anilkumar KK; Manoj VJ; Sagi TM
Med Eng Phys; 2021 Dec; 98():8-19. PubMed ID: 34848042
[TBL] [Abstract][Full Text] [Related]
12. A deep learning method for classifying mammographic breast density categories.
Mohamed AA; Berg WA; Peng H; Luo Y; Jankowitz RC; Wu S
Med Phys; 2018 Jan; 45(1):314-321. PubMed ID: 29159811
[TBL] [Abstract][Full Text] [Related]
13. Rapid Assessment of Acute Ischemic Stroke by Computed Tomography Using Deep Convolutional Neural Networks.
Lo CM; Hung PH; Lin DT
J Digit Imaging; 2021 Jun; 34(3):637-646. PubMed ID: 33963421
[TBL] [Abstract][Full Text] [Related]
14. Fusing hand-crafted and deep-learning features in a convolutional neural network model to identify prostate cancer in pathology images.
Huang X; Li Z; Zhang M; Gao S
Front Oncol; 2022; 12():994950. PubMed ID: 36237311
[TBL] [Abstract][Full Text] [Related]
15. Deep convolutional neural networks for multiple histologic types of ovarian tumors classification in ultrasound images.
Wu M; Cui G; Lv S; Chen L; Tian Z; Yang M; Bai W
Front Oncol; 2023; 13():1154200. PubMed ID: 37427129
[TBL] [Abstract][Full Text] [Related]
16. Deep Learning and Transfer Learning for Optic Disc Laterality Detection: Implications for Machine Learning in Neuro-Ophthalmology.
Liu TYA; Ting DSW; Yi PH; Wei J; Zhu H; Subramanian PS; Li T; Hui FK; Hager GD; Miller NR
J Neuroophthalmol; 2020 Jun; 40(2):178-184. PubMed ID: 31453913
[TBL] [Abstract][Full Text] [Related]
17. Deep learning-based multi-model approach on electron microscopy image of renal biopsy classification.
Zhang J; Zhang A
BMC Nephrol; 2023 May; 24(1):132. PubMed ID: 37161367
[TBL] [Abstract][Full Text] [Related]
18. OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications.
Prahs P; Radeck V; Mayer C; Cvetkov Y; Cvetkova N; Helbig H; Märker D
Graefes Arch Clin Exp Ophthalmol; 2018 Jan; 256(1):91-98. PubMed ID: 29127485
[TBL] [Abstract][Full Text] [Related]
19. Machine Learning-Aided Chronic Kidney Disease Diagnosis Based on Ultrasound Imaging Integrated with Computer-Extracted Measurable Features.
Lee S; Kang M; Byeon K; Lee SE; Lee IH; Kim YA; Kang SW; Park JT
J Digit Imaging; 2022 Oct; 35(5):1091-1100. PubMed ID: 35411524
[TBL] [Abstract][Full Text] [Related]
20. Deep Semantic Segmentation of Kidney and Space-Occupying Lesion Area Based on SCNN and ResNet Models Combined with SIFT-Flow Algorithm.
Xia KJ; Yin HS; Zhang YD
J Med Syst; 2018 Nov; 43(1):2. PubMed ID: 30456668
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
