227 related articles for article (PubMed ID: 32550270)
21. Histological subtypes of hepatocellular carcinoma are related to gene mutations and molecular tumour classification.
Calderaro J; Couchy G; Imbeaud S; Amaddeo G; Letouzé E; Blanc JF; Laurent C; Hajji Y; Azoulay D; Bioulac-Sage P; Nault JC; Zucman-Rossi J
J Hepatol; 2017 Oct; 67(4):727-738. PubMed ID: 28532995
[TBL] [Abstract][Full Text] [Related]
22. Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detection.
Silva-Rodríguez J; Colomer A; Sales MA; Molina R; Naranjo V
Comput Methods Programs Biomed; 2020 Oct; 195():105637. PubMed ID: 32653747
[TBL] [Abstract][Full Text] [Related]
23. Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network.
Alom MZ; Yakopcic C; Nasrin MS; Taha TM; Asari VK
J Digit Imaging; 2019 Aug; 32(4):605-617. PubMed ID: 30756265
[TBL] [Abstract][Full Text] [Related]
24. Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT.
Coy H; Hsieh K; Wu W; Nagarajan MB; Young JR; Douek ML; Brown MS; Scalzo F; Raman SS
Abdom Radiol (NY); 2019 Jun; 44(6):2009-2020. PubMed ID: 30778739
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. Multiphase convolutional dense network for the classification of focal liver lesions on dynamic contrast-enhanced computed tomography.
Cao SE; Zhang LQ; Kuang SC; Shi WQ; Hu B; Xie SD; Chen YN; Liu H; Chen SM; Jiang T; Ye M; Zhang HX; Wang J
World J Gastroenterol; 2020 Jul; 26(25):3660-3672. PubMed ID: 32742134
[TBL] [Abstract][Full Text] [Related]
27. Automated classification of gastric neoplasms in endoscopic images using a convolutional neural network.
Cho BJ; Bang CS; Park SW; Yang YJ; Seo SI; Lim H; Shin WG; Hong JT; Yoo YT; Hong SH; Choi JH; Lee JJ; Baik GH
Endoscopy; 2019 Dec; 51(12):1121-1129. PubMed ID: 31443108
[TBL] [Abstract][Full Text] [Related]
28. Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis.
Kosaraju SC; Hao J; Koh HM; Kang M
Methods; 2020 Jul; 179():3-13. PubMed ID: 32442672
[TBL] [Abstract][Full Text] [Related]
29. Deep Learning for Accurate Diagnosis of Liver Tumor Based on Magnetic Resonance Imaging and Clinical Data.
Zhen SH; Cheng M; Tao YB; Wang YF; Juengpanich S; Jiang ZY; Jiang YK; Yan YY; Lu W; Lue JM; Qian JH; Wu ZY; Sun JH; Lin H; Cai XJ
Front Oncol; 2020; 10():680. PubMed ID: 32547939
[No Abstract] [Full Text] [Related]
30. 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]
31. Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images.
Nir G; Karimi D; Goldenberg SL; Fazli L; Skinnider BF; Tavassoli P; Turbin D; Villamil CF; Wang G; Thompson DJS; Black PC; Salcudean SE
JAMA Netw Open; 2019 Mar; 2(3):e190442. PubMed ID: 30848813
[TBL] [Abstract][Full Text] [Related]
32. 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]
33. Classification and Prognosis Prediction from Histopathological Images of Hepatocellular Carcinoma by a Fully Automated Pipeline Based on Machine Learning.
Liao H; Xiong T; Peng J; Xu L; Liao M; Zhang Z; Wu Z; Yuan K; Zeng Y
Ann Surg Oncol; 2020 Jul; 27(7):2359-2369. PubMed ID: 31916093
[TBL] [Abstract][Full Text] [Related]
34. Recognition of peripheral blood cell images using convolutional neural networks.
Acevedo A; Alférez S; Merino A; Puigví L; Rodellar J
Comput Methods Programs Biomed; 2019 Oct; 180():105020. PubMed ID: 31425939
[TBL] [Abstract][Full Text] [Related]
35. A deep dive into understanding tumor foci classification using multiparametric MRI based on convolutional neural network.
Zong W; Lee JK; Liu C; Carver EN; Feldman AM; Janic B; Elshaikh MA; Pantelic MV; Hearshen D; Chetty IJ; Movsas B; Wen N
Med Phys; 2020 Sep; 47(9):4077-4086. PubMed ID: 32449176
[TBL] [Abstract][Full Text] [Related]
36. A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.
Pang S; Yu Z; Orgun MA
Comput Methods Programs Biomed; 2017 Mar; 140():283-293. PubMed ID: 28254085
[TBL] [Abstract][Full Text] [Related]
37. Skin lesion classification with ensembles of deep convolutional neural networks.
Harangi B
J Biomed Inform; 2018 Oct; 86():25-32. PubMed ID: 30103029
[TBL] [Abstract][Full Text] [Related]
38. Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study.
Jiang M; Zhang D; Tang SC; Luo XM; Chuan ZR; Lv WZ; Jiang F; Ni XJ; Cui XW; Dietrich CF
Eur Radiol; 2021 Jun; 31(6):3673-3682. PubMed ID: 33226454
[TBL] [Abstract][Full Text] [Related]
39. Multistage classification of oral histopathological images using improved residual network.
Panigrahi S; Bhuyan R; Kumar K; Nayak J; Swarnkar T
Math Biosci Eng; 2022 Jan; 19(2):1909-1925. PubMed ID: 35135235
[TBL] [Abstract][Full Text] [Related]
40. Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning.
Tabibu S; Vinod PK; Jawahar CV
Sci Rep; 2019 Jul; 9(1):10509. PubMed ID: 31324828
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
