172 related articles for article (PubMed ID: 36138422)
1. Utility of the deep learning technique for the diagnosis of orbital invasion on CT in patients with a nasal or sinonasal tumor.
Nakagawa J; Fujima N; Hirata K; Tang M; Tsuneta S; Suzuki J; Harada T; Ikebe Y; Homma A; Kano S; Minowa K; Kudo K
Cancer Imaging; 2022 Sep; 22(1):52. PubMed ID: 36138422
[TBL] [Abstract][Full Text] [Related]
2. Diagnosis of skull-base invasion by nasopharyngeal tumors on CT with a deep-learning approach.
Nakagawa J; Fujima N; Hirata K; Harada T; Wakabayashi N; Takano Y; Homma A; Kano S; Minowa K; Kudo K
Jpn J Radiol; 2024 May; 42(5):450-459. PubMed ID: 38280100
[TBL] [Abstract][Full Text] [Related]
3. [A preliminary investigation on a deep learning convolutional neural networks based pulmonary tuberculosis CT diagnostic model].
Wu SC; Wang XJ; Ji JY; Geng G; Zhang ZH; Hou DL
Zhonghua Jie He He Hu Xi Za Zhi; 2021 May; 44(5):450-455. PubMed ID: 34865365
[No Abstract] [Full Text] [Related]
4. A comparison between deep learning convolutional neural networks and radiologists in the differentiation of benign and malignant thyroid nodules on CT images.
Zhao HB; Liu C; Ye J; Chang LF; Xu Q; Shi BW; Liu LL; Yin YL; Shi BB
Endokrynol Pol; 2021; 72(3):217-225. PubMed ID: 33619712
[TBL] [Abstract][Full Text] [Related]
5. Utility of deep learning for the diagnosis of otosclerosis on temporal bone CT.
Fujima N; Andreu-Arasa VC; Onoue K; Weber PC; Hubbell RD; Setty BN; Sakai O
Eur Radiol; 2021 Jul; 31(7):5206-5211. PubMed ID: 33409781
[TBL] [Abstract][Full Text] [Related]
6. An automated diagnosis and classification of COVID-19 from chest CT images using a transfer learning-based convolutional neural network.
Baghdadi NA; Malki A; Abdelaliem SF; Magdy Balaha H; Badawy M; Elhosseini M
Comput Biol Med; 2022 May; 144():105383. PubMed ID: 35290811
[TBL] [Abstract][Full Text] [Related]
7. A fully automated rib fracture detection system on chest CT images and its impact on radiologist performance.
Meng XH; Wu DJ; Wang Z; Ma XL; Dong XM; Liu AE; Chen L
Skeletal Radiol; 2021 Sep; 50(9):1821-1828. PubMed ID: 33599801
[TBL] [Abstract][Full Text] [Related]
8. Deep learning with convolutional neural network for estimation of the characterisation of coronary plaques: Validation using IB-IVUS.
Masuda T; Nakaura T; Funama Y; Oda S; Okimoto T; Sato T; Noda N; Yoshiura T; Baba Y; Arao S; Hiratsuka J; Awai K
Radiography (Lond); 2022 Feb; 28(1):61-67. PubMed ID: 34404578
[TBL] [Abstract][Full Text] [Related]
9. Detection of acute rib fractures on CT images with convolutional neural networks: effect of location and type of fracture and reader's experience.
Azuma M; Nakada H; Takei M; Nakamura K; Katsuragawa S; Shinkawa N; Terada T; Masuda R; Hattori Y; Ide T; Kimura A; Shimomura M; Kawano M; Matsumura K; Meiri T; Ochiai H; Hirai T
Emerg Radiol; 2022 Apr; 29(2):317-328. PubMed ID: 34855002
[TBL] [Abstract][Full Text] [Related]
10. Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search.
Ma J; He N; Yoon JH; Ha R; Li J; Ma W; Meng T; Lu L; Schwartz LH; Wu Y; Ye Z; Wu P; Zhao B; Xie C
Eur J Radiol; 2021 Sep; 142():109878. PubMed ID: 34388626
[TBL] [Abstract][Full Text] [Related]
11. [Application of Deep Learning in Differential Diagnosis of Ameloblastoma and Odontogenic Keratocyst Based on Panoramic Radiographs].
Li M; Mu CC; Zhang JY; Li G
Zhongguo Yi Xue Ke Xue Yuan Xue Bao; 2023 Apr; 45(2):273-279. PubMed ID: 37157075
[TBL] [Abstract][Full Text] [Related]
12. Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation.
Liu KL; Wu T; Chen PT; Tsai YM; Roth H; Wu MS; Liao WC; Wang W
Lancet Digit Health; 2020 Jun; 2(6):e303-e313. PubMed ID: 33328124
[TBL] [Abstract][Full Text] [Related]
13. Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network.
Yanagawa M; Niioka H; Kusumoto M; Awai K; Tsubamoto M; Satoh Y; Miyata T; Yoshida Y; Kikuchi N; Hata A; Yamasaki S; Kido S; Nagahara H; Miyake J; Tomiyama N
Eur Radiol; 2021 Apr; 31(4):1978-1986. PubMed ID: 33011879
[TBL] [Abstract][Full Text] [Related]
14. A Deep Convolutional Neural Network With Performance Comparable to Radiologists for Differentiating Between Spinal Schwannoma and Meningioma.
Maki S; Furuya T; Horikoshi T; Yokota H; Mori Y; Ota J; Kawasaki Y; Miyamoto T; Norimoto M; Okimatsu S; Shiga Y; Inage K; Orita S; Takahashi H; Suyari H; Uno T; Ohtori S
Spine (Phila Pa 1976); 2020 May; 45(10):694-700. PubMed ID: 31809468
[TBL] [Abstract][Full Text] [Related]
15. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm.
Lee JH; Kim DH; Jeong SN; Choi SH
J Dent; 2018 Oct; 77():106-111. PubMed ID: 30056118
[TBL] [Abstract][Full Text] [Related]
16. Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.
Walsh SLF; Calandriello L; Silva M; Sverzellati N
Lancet Respir Med; 2018 Nov; 6(11):837-845. PubMed ID: 30232049
[TBL] [Abstract][Full Text] [Related]
17. Application of deep learning as a noninvasive tool to differentiate muscle-invasive bladder cancer and non-muscle-invasive bladder cancer with CT.
Yang Y; Zou X; Wang Y; Ma X
Eur J Radiol; 2021 Jun; 139():109666. PubMed ID: 33798819
[TBL] [Abstract][Full Text] [Related]
18. Impact of deep learning on radiologists and radiology residents in detecting breast cancer on CT: a cross-vendor test study.
Yasaka K; Sato C; Hirakawa H; Fujita N; Kurokawa M; Watanabe Y; Kubo T; Abe O
Clin Radiol; 2024 Jan; 79(1):e41-e47. PubMed ID: 37872026
[TBL] [Abstract][Full Text] [Related]
19. High-resolution CT image analysis based on 3D convolutional neural network can enhance the classification performance of radiologists in classifying pulmonary non-solid nodules.
Zhang T; Wang Y; Sun Y; Yuan M; Zhong Y; Li H; Yu T; Wang J
Eur J Radiol; 2021 Aug; 141():109810. PubMed ID: 34102564
[TBL] [Abstract][Full Text] [Related]
20. Kidney Tumor Detection and Classification Based on Deep Learning Approaches: A New Dataset in CT Scans.
Alzu'bi D; Abdullah M; Hmeidi I; AlAzab R; Gharaibeh M; El-Heis M; Almotairi KH; Forestiero A; Hussein AM; Abualigah L
J Healthc Eng; 2022; 2022():3861161. PubMed ID: 37323471
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]