129 related articles for article (PubMed ID: 35251578)
1. Proposing Novel Data Analytics Method for Anatomical Landmark Identification from Endoscopic Video Frames.
Ayyoubi Nezhad S; Khatibi T; Sohrabi M
J Healthc Eng; 2022; 2022():8151177. PubMed ID: 35251578
[TBL] [Abstract][Full Text] [Related]
2. MAPGI: Accurate identification of anatomical landmarks and diseased tissue in gastrointestinal tract using deep learning.
Cogan T; Cogan M; Tamil L
Comput Biol Med; 2019 Aug; 111():103351. PubMed ID: 31325742
[TBL] [Abstract][Full Text] [Related]
3. Supervised and semi-supervised training of deep convolutional neural networks for gastric landmark detection.
Lopes I; Silva A; Coimbra M; Dinis-Ribeiro M; Libanio D; Renna F
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():2025-2028. PubMed ID: 36086140
[TBL] [Abstract][Full Text] [Related]
4. Real time anatomical landmarks and abnormalities detection in gastrointestinal tract.
Khan Z; Tahir MA
PeerJ Comput Sci; 2023; 9():e1685. PubMed ID: 38192480
[TBL] [Abstract][Full Text] [Related]
5. A systematic evaluation and optimization of automatic detection of ulcers in wireless capsule endoscopy on a large dataset using deep convolutional neural networks.
Wang S; Xing Y; Zhang L; Gao H; Zhang H
Phys Med Biol; 2019 Dec; 64(23):235014. PubMed ID: 31645019
[TBL] [Abstract][Full Text] [Related]
6. Classification of endoscopic image and video frames using distance metric-based learning with interpolated latent features.
Sedighipour Chafjiri F; Mohebbian MR; Wahid KA; Babyn P
Multimed Tools Appl; 2023 Mar; ():1-22. PubMed ID: 37362715
[TBL] [Abstract][Full Text] [Related]
7. Wavelet Transform and Deep Convolutional Neural Network-Based Smart Healthcare System for Gastrointestinal Disease Detection.
Mohapatra S; Nayak J; Mishra M; Pati GK; Naik B; Swarnkar T
Interdiscip Sci; 2021 Jun; 13(2):212-228. PubMed ID: 33566337
[TBL] [Abstract][Full Text] [Related]
8. Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images.
Thambawita V; Strümke I; Hicks SA; Halvorsen P; Parasa S; Riegler MA
Diagnostics (Basel); 2021 Nov; 11(12):. PubMed ID: 34943421
[TBL] [Abstract][Full Text] [Related]
9. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.
Huang W; Xue Y; Wu Y
PLoS One; 2019; 14(7):e0219369. PubMed ID: 31299053
[TBL] [Abstract][Full Text] [Related]
10. Detecting Anatomical Landmarks From Limited Medical Imaging Data Using Two-Stage Task-Oriented Deep Neural Networks.
Zhang J; Liu M; Shen D
IEEE Trans Image Process; 2017 Oct; 26(10):4753-4764. PubMed ID: 28678706
[TBL] [Abstract][Full Text] [Related]
11. Deep Anatomical Context Feature Learning for Cephalometric Landmark Detection.
Oh K; Oh IS; Le VNT; Lee DW
IEEE J Biomed Health Inform; 2021 Mar; 25(3):806-817. PubMed ID: 32750939
[TBL] [Abstract][Full Text] [Related]
12. Discovering Salient Anatomical Landmarks by Predicting Human Gaze.
Droste R; Chatelain P; Drukker L; Sharma H; Papageorghiou AT; Noble JA
Proc IEEE Int Symp Biomed Imaging; 2020 Apr; 2020():1711-1714. PubMed ID: 32489518
[TBL] [Abstract][Full Text] [Related]
13. Deep Learning Methods for Anatomical Landmark Detection in Video Capsule Endoscopy Images.
Adewole S; Yeghyayan M; Hyatt D; Ehsan L; Jablonski J; Copland A; Syed S; Brown D
Proc Future Technol Conf (2020); 2021 Nov; 1288():426-434. PubMed ID: 34693407
[TBL] [Abstract][Full Text] [Related]
14. Object and anatomical feature recognition in surgical video images based on a convolutional neural network.
Bamba Y; Ogawa S; Itabashi M; Shindo H; Kameoka S; Okamoto T; Yamamoto M
Int J Comput Assist Radiol Surg; 2021 Nov; 16(11):2045-2054. PubMed ID: 34169465
[TBL] [Abstract][Full Text] [Related]
15. Development of deep learning framework for anatomical landmark detection and guided dissection line during laparoscopic cholecystectomy.
Smithmaitrie P; Khaonualsri M; Sae-Lim W; Wangkulangkul P; Jearanai S; Cheewatanakornkul S
Heliyon; 2024 Feb; 10(3):e25210. PubMed ID: 38327394
[TBL] [Abstract][Full Text] [Related]
16. Hybrid Models for Endoscopy Image Analysis for Early Detection of Gastrointestinal Diseases Based on Fused Features.
Ahmed IA; Senan EM; Shatnawi HSA
Diagnostics (Basel); 2023 May; 13(10):. PubMed ID: 37238241
[TBL] [Abstract][Full Text] [Related]
17. Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.
Ross T; Zimmerer D; Vemuri A; Isensee F; Wiesenfarth M; Bodenstedt S; Both F; Kessler P; Wagner M; Müller B; Kenngott H; Speidel S; Kopp-Schneider A; Maier-Hein K; Maier-Hein L
Int J Comput Assist Radiol Surg; 2018 Jun; 13(6):925-933. PubMed ID: 29704196
[TBL] [Abstract][Full Text] [Related]
18. A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation.
Laves MH; Bicker J; Kahrs LA; Ortmaier T
Int J Comput Assist Radiol Surg; 2019 Mar; 14(3):483-492. PubMed ID: 30649670
[TBL] [Abstract][Full Text] [Related]
19. Automatic location scheme of anatomical landmarks in 3D head MRI based on the scale attention hourglass network.
Li S; Gong Q; Li H; Chen S; Liu Y; Ruan G; Zhu L; Liu L; Chen H
Comput Methods Programs Biomed; 2022 Feb; 214():106564. PubMed ID: 34894558
[TBL] [Abstract][Full Text] [Related]
20. Human peripheral blood leukocyte classification method based on convolutional neural network and data augmentation.
Wang Y; Cao Y
Med Phys; 2020 Jan; 47(1):142-151. PubMed ID: 31691975
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]