144 related articles for article (PubMed ID: 38214722)
41. 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]
42. Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes.
Burgos-Artizzu XP; Coronado-Gutiérrez D; Valenzuela-Alcaraz B; Bonet-Carne E; Eixarch E; Crispi F; Gratacós E
Sci Rep; 2020 Jun; 10(1):10200. PubMed ID: 32576905
[TBL] [Abstract][Full Text] [Related]
43. A two-stage multiresolution neural network for automatic diagnosis of hepatic echinococcosis from ultrasound images: A multicenter study.
Cheng J; Wang H; Li R; Li X; Zhou X; Yang X; Wang Y; Xiong L; Fan H; Wang T; Li M; Ni D
Med Phys; 2022 May; 49(5):3199-3212. PubMed ID: 35192193
[TBL] [Abstract][Full Text] [Related]
44. Agreement of two pre-trained deep-learning neural networks built with transfer learning with six pathologists on 6000 patches of prostate cancer from Gleason2019 Challenge.
Şerbănescu MS; Oancea CN; Streba CT; Pleşea IE; Pirici D; Streba L; Pleşea RM
Rom J Morphol Embryol; 2020; 61(2):513-519. PubMed ID: 33544803
[TBL] [Abstract][Full Text] [Related]
45. Automatic recognition of bladder tumours using deep learning technology and its clinical application.
Yang R; Du Y; Weng X; Chen Z; Wang S; Liu X
Int J Med Robot; 2021 Apr; 17(2):e2194. PubMed ID: 33119212
[TBL] [Abstract][Full Text] [Related]
46. A comparative study for glioma classification using deep convolutional neural networks.
Özcan H; Emiroğlu BG; Sabuncuoğlu H; Özdoğan S; Soyer A; Saygı T
Math Biosci Eng; 2021 Jan; 18(2):1550-1572. PubMed ID: 33757198
[TBL] [Abstract][Full Text] [Related]
47. BUS-Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets.
Thomas C; Byra M; Marti R; Yap MH; Zwiggelaar R
Med Phys; 2023 May; 50(5):3223-3243. PubMed ID: 36794706
[TBL] [Abstract][Full Text] [Related]
48. An effective convolutional neural network for classification of benign and malignant breast and thyroid tumors from ultrasound images.
Tian R; Yu M; Liao L; Zhang C; Zhao J; Sang L; Qian W; Wang Z; Huang L; Ma H
Phys Eng Sci Med; 2023 Sep; 46(3):995-1013. PubMed ID: 37195403
[TBL] [Abstract][Full Text] [Related]
49. Risks of feature leakage and sample size dependencies in deep feature extraction for breast mass classification.
Samala RK; Chan HP; Hadjiiski L; Helvie MA
Med Phys; 2021 Jun; 48(6):2827-2837. PubMed ID: 33368376
[TBL] [Abstract][Full Text] [Related]
50. Enhancing classification of cells procured from bone marrow aspirate smears using generative adversarial networks and sequential convolutional neural network.
Hazra D; Byun YC; Kim WJ
Comput Methods Programs Biomed; 2022 Sep; 224():107019. PubMed ID: 35878483
[TBL] [Abstract][Full Text] [Related]
51. Automatic Classification of Hepatic Cystic Echinococcosis Using Ultrasound Images and Deep Learning.
Wu M; Yan C; Wang X; Liu Q; Liu Z; Song T
J Ultrasound Med; 2022 Jan; 41(1):163-174. PubMed ID: 33710638
[TBL] [Abstract][Full Text] [Related]
52. Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks.
Wang L; Zhang L; Zhu M; Qi X; Yi Z
Med Image Anal; 2020 Apr; 61():101665. PubMed ID: 32062156
[TBL] [Abstract][Full Text] [Related]
53. Classification of rotator cuff tears in ultrasound images using deep learning models.
Ho TT; Kim GT; Kim T; Choi S; Park EK
Med Biol Eng Comput; 2022 May; 60(5):1269-1278. PubMed ID: 35043367
[TBL] [Abstract][Full Text] [Related]
54. Enhancing Skin Cancer Classification using Efficient Net B0-B7 through Convolutional Neural Networks and Transfer Learning with Patient-Specific Data.
K K; S K; K J A; B C
Asian Pac J Cancer Prev; 2024 May; 25(5):1795-1802. PubMed ID: 38809652
[TBL] [Abstract][Full Text] [Related]
55. MediNet: transfer learning approach with MediNet medical visual database.
Reis HC; Turk V; Khoshelham K; Kaya S
Multimed Tools Appl; 2023 Mar; ():1-44. PubMed ID: 37362724
[TBL] [Abstract][Full Text] [Related]
56. Application of Convolutional Neural Networks for Automated Ulcer Detection in Wireless Capsule Endoscopy Images.
Alaskar H; Hussain A; Al-Aseem N; Liatsis P; Al-Jumeily D
Sensors (Basel); 2019 Mar; 19(6):. PubMed ID: 30871162
[TBL] [Abstract][Full Text] [Related]
57. Breast Tumor Classification in Ultrasound Images Using Combined Deep and Handcrafted Features.
Daoud MI; Abdel-Rahman S; Bdair TM; Al-Najar MS; Al-Hawari FH; Alazrai R
Sensors (Basel); 2020 Nov; 20(23):. PubMed ID: 33265900
[TBL] [Abstract][Full Text] [Related]
58. Are All Deep Learning Architectures Alike for Point-of-Care Ultrasound?: Evidence From a Cardiac Image Classification Model Suggests Otherwise.
Blaivas M; Blaivas L
J Ultrasound Med; 2020 Jun; 39(6):1187-1194. PubMed ID: 31872477
[TBL] [Abstract][Full Text] [Related]
59. Machine-learning-based automatic identification of fetal abdominal circumference from ultrasound images.
Kim B; Kim KC; Park Y; Kwon JY; Jang J; Seo JK
Physiol Meas; 2018 Oct; 39(10):105007. PubMed ID: 30226815
[TBL] [Abstract][Full Text] [Related]
60. 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]
[Previous] [Next] [New Search]