250 related articles for article (PubMed ID: 35157332)
1. Deep learning-based body part recognition algorithm for three-dimensional medical images.
Ouyang Z; Zhang P; Pan W; Li Q
Med Phys; 2022 May; 49(5):3067-3079. PubMed ID: 35157332
[TBL] [Abstract][Full Text] [Related]
2. BRR-Net: A tandem architectural CNN-RNN for automatic body region localization in CT images.
Agrawal V; Udupa J; Tong Y; Torigian D
Med Phys; 2020 Oct; 47(10):5020-5031. PubMed ID: 32761899
[TBL] [Abstract][Full Text] [Related]
3. Application of Imaging Examination Based on Deep Learning in the Diagnosis of Viral Senile Pneumonia.
Deng X; Ge X; Xue Q; Liu H
Contrast Media Mol Imaging; 2022; 2022():6964283. PubMed ID: 35694707
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Bodypart Recognition Using Multi-stage Deep Learning.
Yan Z; Zhan Y; Peng Z; Liao S; Shinagawa Y; Metaxas DN; Zhou XS
Inf Process Med Imaging; 2015; 24():449-61. PubMed ID: 26221694
[TBL] [Abstract][Full Text] [Related]
6. A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images.
Wang Y; Qiu Y; Thai T; Moore K; Liu H; Zheng B
Comput Methods Programs Biomed; 2017 Jun; 144():97-104. PubMed ID: 28495009
[TBL] [Abstract][Full Text] [Related]
7. Phase recognition in contrast-enhanced CT scans based on deep learning and random sampling.
Dao BT; Nguyen TV; Pham HH; Nguyen HQ
Med Phys; 2022 Jul; 49(7):4518-4528. PubMed ID: 35428990
[TBL] [Abstract][Full Text] [Related]
8. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH
Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353
[TBL] [Abstract][Full Text] [Related]
9. Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.
Ye H; Gao F; Yin Y; Guo D; Zhao P; Lu Y; Wang X; Bai J; Cao K; Song Q; Zhang H; Chen W; Guo X; Xia J
Eur Radiol; 2019 Nov; 29(11):6191-6201. PubMed ID: 31041565
[TBL] [Abstract][Full Text] [Related]
10. Development and External Validation of a Deep Learning Algorithm to Identify and Localize Subarachnoid Hemorrhage on CT Scans.
Thanellas A; Peura H; Lavinto M; Ruokola T; Vieli M; Staartjes VE; Winklhofer S; Serra C; Regli L; Korja M
Neurology; 2023 Mar; 100(12):e1257-e1266. PubMed ID: 36639236
[TBL] [Abstract][Full Text] [Related]
11. Brain MRI analysis using a deep learning based evolutionary approach.
Shahamat H; Saniee Abadeh M
Neural Netw; 2020 Jun; 126():218-234. PubMed ID: 32259762
[TBL] [Abstract][Full Text] [Related]
12. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
Zhu W; Huang Y; Zeng L; Chen X; Liu Y; Qian Z; Du N; Fan W; Xie X
Med Phys; 2019 Feb; 46(2):576-589. PubMed ID: 30480818
[TBL] [Abstract][Full Text] [Related]
13. Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application.
Papandrianos N; Papageorgiou E; Anagnostis A; Papageorgiou K
PLoS One; 2020; 15(8):e0237213. PubMed ID: 32797099
[TBL] [Abstract][Full Text] [Related]
14. Automatic Segmentation of Multiple Organs on 3D CT Images by Using Deep Learning Approaches.
Zhou X
Adv Exp Med Biol; 2020; 1213():135-147. PubMed ID: 32030668
[TBL] [Abstract][Full Text] [Related]
15. OzNet: A New Deep Learning Approach for Automated Classification of COVID-19 Computed Tomography Scans.
Ozaltin O; Yeniay O; Subasi A
Big Data; 2023 Dec; 11(6):420-436. PubMed ID: 36927081
[TBL] [Abstract][Full Text] [Related]
16. Diagnosis of Alzheimer's disease using structure highlighting key slice stacking and transfer learning.
Ban Y; Zhang X; Lao H
Med Phys; 2022 Sep; 49(9):5855-5869. PubMed ID: 35894542
[TBL] [Abstract][Full Text] [Related]
17. Performance of a deep learning-based CT image denoising method: Generalizability over dose, reconstruction kernel, and slice thickness.
Zeng R; Lin CY; Li Q; Jiang L; Skopec M; Fessler JA; Myers KJ
Med Phys; 2022 Feb; 49(2):836-853. PubMed ID: 34954845
[TBL] [Abstract][Full Text] [Related]
18. Lung cancer histology classification from CT images based on radiomics and deep learning models.
Marentakis P; Karaiskos P; Kouloulias V; Kelekis N; Argentos S; Oikonomopoulos N; Loukas C
Med Biol Eng Comput; 2021 Jan; 59(1):215-226. PubMed ID: 33411267
[TBL] [Abstract][Full Text] [Related]
19. Deep learning enabled ultra-fast-pitch acquisition in clinical X-ray computed tomography.
Gong H; Ren L; Hsieh SS; McCollough CH; Yu L
Med Phys; 2021 Oct; 48(10):5712-5726. PubMed ID: 34415068
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
