239 related articles for article (PubMed ID: 31946767)
1. Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset.
Gozes O; Greenspan H
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():4076-4079. PubMed ID: 31946767
[TBL] [Abstract][Full Text] [Related]
2. Targeted transfer learning to improve performance in small medical physics datasets.
Romero M; Interian Y; Solberg T; Valdes G
Med Phys; 2020 Dec; 47(12):6246-6256. PubMed ID: 33007112
[TBL] [Abstract][Full Text] [Related]
3. Deep learning, reusable and problem-based architectures for detection of consolidation on chest X-ray images.
Behzadi-Khormouji H; Rostami H; Salehi S; Derakhshande-Rishehri T; Masoumi M; Salemi S; Keshavarz A; Gholamrezanezhad A; Assadi M; Batouli A
Comput Methods Programs Biomed; 2020 Mar; 185():105162. PubMed ID: 31715332
[TBL] [Abstract][Full Text] [Related]
4. CheXNet and feature pyramid network: a fusion deep learning architecture for multilabel chest X-Ray clinical diagnoses classification.
Hasanah U; Avian C; Darmawan JT; Bachroin N; Faisal M; Prakosa SW; Leu JS; Tsai CT
Int J Cardiovasc Imaging; 2024 Apr; 40(4):709-722. PubMed ID: 38150139
[TBL] [Abstract][Full Text] [Related]
5. A Study on Tuberculosis Classification in Chest X-ray Using Deep Residual Attention Networks
Zhang R; Duan H; Cheng J; Zheng Y
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1552-1555. PubMed ID: 33018288
[TBL] [Abstract][Full Text] [Related]
6. An efficient deep learning-based framework for tuberculosis detection using chest X-ray images.
Iqbal A; Usman M; Ahmed Z
Tuberculosis (Edinb); 2022 Sep; 136():102234. PubMed ID: 35872406
[TBL] [Abstract][Full Text] [Related]
7. Brain tumor classification for MR images using transfer learning and fine-tuning.
Swati ZNK; Zhao Q; Kabir M; Ali F; Ali Z; Ahmed S; Lu J
Comput Med Imaging Graph; 2019 Jul; 75():34-46. PubMed ID: 31150950
[TBL] [Abstract][Full Text] [Related]
8. SDFN: Segmentation-based deep fusion network for thoracic disease classification in chest X-ray images.
Liu H; Wang L; Nan Y; Jin F; Wang Q; Pu J
Comput Med Imaging Graph; 2019 Jul; 75():66-73. PubMed ID: 31174100
[TBL] [Abstract][Full Text] [Related]
9. Computer-Aided detection of tuberculosis from X-ray images using CNN and PatternNet classifier.
Abraham B; Mohan J; John SM; Ramachandran S
J Xray Sci Technol; 2023; 31(4):699-711. PubMed ID: 37182860
[TBL] [Abstract][Full Text] [Related]
10. A Novel and Robust Approach to Detect Tuberculosis Using Transfer Learning.
Faruk O; Ahmed E; Ahmed S; Tabassum A; Tazin T; Bourouis S; Monirujjaman Khan M
J Healthc Eng; 2021; 2021():1002799. PubMed ID: 34868509
[TBL] [Abstract][Full Text] [Related]
11. Deep Mining External Imperfect Data for Chest X-Ray Disease Screening.
Luo L; Yu L; Chen H; Liu Q; Wang X; Xu J; Heng PA
IEEE Trans Med Imaging; 2020 Nov; 39(11):3583-3594. PubMed ID: 32746106
[TBL] [Abstract][Full Text] [Related]
12. Chest x-ray automated triage: A semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning architectures.
Mosquera C; Diaz FN; Binder F; Rabellino JM; Benitez SE; Beresñak AD; Seehaus A; Ducrey G; Ocantos JA; Luna DR
Comput Methods Programs Biomed; 2021 Jul; 206():106130. PubMed ID: 34023576
[TBL] [Abstract][Full Text] [Related]
13. Combining Deep Learning and Knowledge-driven Reasoning for Chest X-Ray Findings Detection.
Jadhav A; Wong KCL; Wu JT; Moradi M; Syeda-Mahmood T
AMIA Annu Symp Proc; 2020; 2020():593-601. PubMed ID: 33936433
[TBL] [Abstract][Full Text] [Related]
14. TEM virus images: Benchmark dataset and deep learning classification.
Matuszewski DJ; Sintorn IM
Comput Methods Programs Biomed; 2021 Sep; 209():106318. PubMed ID: 34375851
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Triple attention learning for classification of 14 thoracic diseases using chest radiography.
Wang H; Wang S; Qin Z; Zhang Y; Li R; Xia Y
Med Image Anal; 2021 Jan; 67():101846. PubMed ID: 33129145
[TBL] [Abstract][Full Text] [Related]
17. Effect of Training Data Volume on Performance of Convolutional Neural Network Pneumothorax Classifiers.
Thian YL; Ng DW; Hallinan JTPD; Jagmohan P; Sia SY; Mohamed JSA; Quek ST; Feng M
J Digit Imaging; 2022 Aug; 35(4):881-892. PubMed ID: 35239091
[TBL] [Abstract][Full Text] [Related]
18. Thorax-Net: An Attention Regularized Deep Neural Network for Classification of Thoracic Diseases on Chest Radiography.
Wang H; Jia H; Lu L; Xia Y
IEEE J Biomed Health Inform; 2020 Feb; 24(2):475-485. PubMed ID: 31329567
[TBL] [Abstract][Full Text] [Related]
19. Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years Review.
Santosh KC; Allu S; Rajaraman S; Antani S
J Med Syst; 2022 Oct; 46(11):82. PubMed ID: 36241922
[TBL] [Abstract][Full Text] [Related]
20. Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19.
Nabulsi Z; Sellergren A; Jamshy S; Lau C; Santos E; Kiraly AP; Ye W; Yang J; Pilgrim R; Kazemzadeh S; Yu J; Kalidindi SR; Etemadi M; Garcia-Vicente F; Melnick D; Corrado GS; Peng L; Eswaran K; Tse D; Beladia N; Liu Y; Chen PC; Shetty S
Sci Rep; 2021 Sep; 11(1):15523. PubMed ID: 34471144
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
