1698 related articles for article (PubMed ID: 32485986)
1. Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images.
Brehar R; Mitrea DA; Vancea F; Marita T; Nedevschi S; Lupsor-Platon M; Rotaru M; Badea RI
Sensors (Basel); 2020 May; 20(11):. PubMed ID: 32485986
[TBL] [Abstract][Full Text] [Related]
2. Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques.
Mitrea DA; Brehar R; Nedevschi S; Lupsor-Platon M; Socaciu M; Badea R
Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904722
[TBL] [Abstract][Full Text] [Related]
3. LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images.
Aatresh AA; Alabhya K; Lal S; Kini J; Saxena PUP
Int J Comput Assist Radiol Surg; 2021 Sep; 16(9):1549-1563. PubMed ID: 34053009
[TBL] [Abstract][Full Text] [Related]
4. Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods.
Mitrea D; Badea R; Mitrea P; Brad S; Nedevschi S
Sensors (Basel); 2021 Mar; 21(6):. PubMed ID: 33801125
[TBL] [Abstract][Full Text] [Related]
5. Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks.
Ouhmich F; Agnus V; Noblet V; Heitz F; Pessaux P
Int J Comput Assist Radiol Surg; 2019 Aug; 14(8):1275-1284. PubMed ID: 31041697
[TBL] [Abstract][Full Text] [Related]
6. White blood cells detection and classification based on regional convolutional neural networks.
Kutlu H; Avci E; Özyurt F
Med Hypotheses; 2020 Feb; 135():109472. PubMed ID: 31760248
[TBL] [Abstract][Full Text] [Related]
7. Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.
Li S; Jiang H; Pang W
Comput Biol Med; 2017 May; 84():156-167. PubMed ID: 28365546
[TBL] [Abstract][Full Text] [Related]
8. Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features.
Wang CJ; Hamm CA; Savic LJ; Ferrante M; Schobert I; Schlachter T; Lin M; Weinreb JC; Duncan JS; Chapiro J; Letzen B
Eur Radiol; 2019 Jul; 29(7):3348-3357. PubMed ID: 31093705
[TBL] [Abstract][Full Text] [Related]
9. An experimental study on breast lesion detection and classification from ultrasound images using deep learning architectures.
Cao Z; Duan L; Yang G; Yue T; Chen Q
BMC Med Imaging; 2019 Jul; 19(1):51. PubMed ID: 31262255
[TBL] [Abstract][Full Text] [Related]
10. DLNLF-net: Denoised local and non-local deep features fusion network for malignancy characterization of hepatocellular carcinoma.
Huang H; Xie Y; Wang G; Zhang L; Zhou W
Comput Methods Programs Biomed; 2022 Dec; 227():107201. PubMed ID: 36335751
[TBL] [Abstract][Full Text] [Related]
11. Grading of hepatocellular carcinoma based on diffusion weighted images with multiple b-values using convolutional neural networks.
Zhou W; Wang G; Xie G; Zhang L
Med Phys; 2019 Sep; 46(9):3951-3960. PubMed ID: 31169907
[TBL] [Abstract][Full Text] [Related]
12. Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI.
Hamm CA; Wang CJ; Savic LJ; Ferrante M; Schobert I; Schlachter T; Lin M; Duncan JS; Weinreb JC; Chapiro J; Letzen B
Eur Radiol; 2019 Jul; 29(7):3338-3347. PubMed ID: 31016442
[TBL] [Abstract][Full Text] [Related]
13. Computer-aided diagnosis of cirrhosis and hepatocellular carcinoma using multi-phase abdomen CT.
Nayak A; Baidya Kayal E; Arya M; Culli J; Krishan S; Agarwal S; Mehndiratta A
Int J Comput Assist Radiol Surg; 2019 Aug; 14(8):1341-1352. PubMed ID: 31062266
[TBL] [Abstract][Full Text] [Related]
14. Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features.
Xu Y; Jia Z; Wang LB; Ai Y; Zhang F; Lai M; Chang EI
BMC Bioinformatics; 2017 May; 18(1):281. PubMed ID: 28549410
[TBL] [Abstract][Full Text] [Related]
15. Automated classification of hepatocellular carcinoma differentiation using multiphoton microscopy and deep learning.
Lin H; Wei C; Wang G; Chen H; Lin L; Ni M; Chen J; Zhuo S
J Biophotonics; 2019 Jul; 12(7):e201800435. PubMed ID: 30868728
[TBL] [Abstract][Full Text] [Related]
16. Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.
P B S; Faruqi F; K S H; Kudva R
Asian Pac J Cancer Prev; 2019 Nov; 20(11):3447-3456. PubMed ID: 31759371
[TBL] [Abstract][Full Text] [Related]
17. A comparative study of pre-trained convolutional neural networks for semantic segmentation of breast tumors in ultrasound.
Gómez-Flores W; Coelho de Albuquerque Pereira W
Comput Biol Med; 2020 Nov; 126():104036. PubMed ID: 33059238
[TBL] [Abstract][Full Text] [Related]
18. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification.
Al-Antari MA; Al-Masni MA; Choi MT; Han SM; Kim TS
Int J Med Inform; 2018 Sep; 117():44-54. PubMed ID: 30032964
[TBL] [Abstract][Full Text] [Related]
19. Joint segmentation and classification of hepatic lesions in ultrasound images using deep learning.
Ryu H; Shin SY; Lee JY; Lee KM; Kang HJ; Yi J
Eur Radiol; 2021 Nov; 31(11):8733-8742. PubMed ID: 33881566
[TBL] [Abstract][Full Text] [Related]
20. Deep Convolutional Neural Network for Ulcer Recognition in Wireless Capsule Endoscopy: Experimental Feasibility and Optimization.
Wang S; Xing Y; Zhang L; Gao H; Zhang H
Comput Math Methods Med; 2019; 2019():7546215. PubMed ID: 31641370
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]