117 related articles for article (PubMed ID: 37715993)
21. EPANet-KD: Efficient progressive attention network for fine-grained provincial village classification via knowledge distillation.
Zhang C; Liu C; Gong H; Teng J
PLoS One; 2024; 19(2):e0298452. PubMed ID: 38359020
[TBL] [Abstract][Full Text] [Related]
22. Weakly supervised semantic segmentation of histological tissue via attention accumulation and pixel-level contrast learning.
Han Y; Cheng L; Huang G; Zhong G; Li J; Yuan X; Liu H; Li J; Zhou J; Cai M
Phys Med Biol; 2023 Feb; 68(4):. PubMed ID: 36577142
[No Abstract] [Full Text] [Related]
23. A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.
Zhao X; Wang X; Xia W; Li Q; Zhou L; Li Q; Zhang R; Cai J; Jian J; Fan L; Wang W; Bai H; Li Z; Xiao Y; Tang Y; Gao X; Liu S
Lung Cancer; 2020 Jul; 145():10-17. PubMed ID: 32387813
[TBL] [Abstract][Full Text] [Related]
24. DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.
Kadirappa R; S D; R P; Ko SB
Microsc Res Tech; 2024 Feb; 87(2):229-256. PubMed ID: 37750465
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. Prediction of high-grade patterns of stage IA lung invasive adenocarcinoma based on high-resolution CT features: a bicentric study.
Dong H; Yin LK; Qiu YG; Wang XB; Yang JJ; Lou CC; Ye XD
Eur Radiol; 2023 Jun; 33(6):3931-3940. PubMed ID: 36600124
[TBL] [Abstract][Full Text] [Related]
27. Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation.
Jiang J; Riyahi Alam S; Chen I; Zhang P; Rimner A; Deasy JO; Veeraraghavan H
Med Phys; 2021 Jul; 48(7):3702-3713. PubMed ID: 33905558
[TBL] [Abstract][Full Text] [Related]
28. Non-invasive classification of non-small cell lung cancer: a comparison between random forest models utilising radiomic and semantic features.
Bashir U; Kawa B; Siddique M; Mak SM; Nair A; Mclean E; Bille A; Goh V; Cook G
Br J Radiol; 2019 Jul; 92(1099):20190159. PubMed ID: 31166787
[TBL] [Abstract][Full Text] [Related]
29. A novel radiomic nomogram for predicting epidermal growth factor receptor mutation in peripheral lung adenocarcinoma.
Lu X; Li M; Zhang H; Hua S; Meng F; Yang H; Li X; Cao D
Phys Med Biol; 2020 Mar; 65(5):055012. PubMed ID: 31978901
[TBL] [Abstract][Full Text] [Related]
30. A semi-supervised learning framework for micropapillary adenocarcinoma detection.
Gao Y; Ding Y; Xiao W; Yao Z; Zhou X; Sui X; Zhao Y; Zheng Y
Int J Comput Assist Radiol Surg; 2022 Apr; 17(4):639-648. PubMed ID: 35149953
[TBL] [Abstract][Full Text] [Related]
31. Semi-Supervised Deep Transfer Learning for Benign-Malignant Diagnosis of Pulmonary Nodules in Chest CT Images.
Shi F; Chen B; Cao Q; Wei Y; Zhou Q; Zhang R; Zhou Y; Yang W; Wang X; Fan R; Yang F; Chen Y; Li W; Gao Y; Shen D
IEEE Trans Med Imaging; 2022 Apr; 41(4):771-781. PubMed ID: 34705640
[TBL] [Abstract][Full Text] [Related]
32. One-step algorithm for fast-track localization and multi-category classification of histological subtypes in lung cancer.
Qi J; Deng Z; Sun G; Qian S; Liu L; Xu B
Eur J Radiol; 2022 Sep; 154():110443. PubMed ID: 35901600
[TBL] [Abstract][Full Text] [Related]
33. Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method.
Jung H; Kim B; Lee I; Lee J; Kang J
BMC Med Imaging; 2018 Dec; 18(1):48. PubMed ID: 30509191
[TBL] [Abstract][Full Text] [Related]
34. ViSTA: A Novel Network Improving Lung Adenocarcinoma Invasiveness Prediction from Follow-Up CT Series.
Zhao W; Sun Y; Kuang K; Yang J; Li G; Ni B; Jiang Y; Jiang B; Liu J; Li M
Cancers (Basel); 2022 Jul; 14(15):. PubMed ID: 35954342
[TBL] [Abstract][Full Text] [Related]
35. PKDN: Prior Knowledge Distillation Network for bronchoscopy diagnosis.
Yan P; Sun W; Li X; Li M; Jiang Y; Luo H
Comput Biol Med; 2023 Nov; 166():107486. PubMed ID: 37757599
[TBL] [Abstract][Full Text] [Related]
36. Multi-scale, domain knowledge-guided attention + random forest: a two-stage deep learning-based multi-scale guided attention models to diagnose idiopathic pulmonary fibrosis from computed tomography images.
Yu W; Zhou H; Choi Y; Goldin JG; Teng P; Wong WK; McNitt-Gray MF; Brown MS; Kim GHJ
Med Phys; 2023 Feb; 50(2):894-905. PubMed ID: 36254789
[TBL] [Abstract][Full Text] [Related]
37. Effective lung nodule detection using deep CNN with dual attention mechanisms.
UrRehman Z; Qiang Y; Wang L; Shi Y; Yang Q; Khattak SU; Aftab R; Zhao J
Sci Rep; 2024 Feb; 14(1):3934. PubMed ID: 38365831
[TBL] [Abstract][Full Text] [Related]
38. DistilIQA: Distilling Vision Transformers for no-reference perceptual CT image quality assessment.
Baldeon-Calisto M; Rivera-Velastegui F; Lai-Yuen SK; Riofrío D; Pérez-Pérez N; Benítez D; Flores-Moyano R
Comput Biol Med; 2024 Jul; 177():108670. PubMed ID: 38838558
[TBL] [Abstract][Full Text] [Related]
39. Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.
Rikhari H; Baidya Kayal E; Ganguly S; Sasi A; Sharma S; Dheeksha DS; Saini M; Rangarajan K; Bakhshi S; Kandasamy D; Mehndiratta A
Int J Comput Assist Radiol Surg; 2024 Feb; 19(2):261-272. PubMed ID: 37594684
[TBL] [Abstract][Full Text] [Related]
40. An improved 3-D attention CNN with hybrid loss and feature fusion for pulmonary nodule classification.
Huang YS; Wang TC; Huang SZ; Zhang J; Chen HM; Chang YC; Chang RF
Comput Methods Programs Biomed; 2023 Feb; 229():107278. PubMed ID: 36463674
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]