579 related articles for article (PubMed ID: 32034633)
21. A review on lung boundary detection in chest X-rays.
Candemir S; Antani S
Int J Comput Assist Radiol Surg; 2019 Apr; 14(4):563-576. PubMed ID: 30730032
[TBL] [Abstract][Full Text] [Related]
22. Extracting Lungs from CT Images via Deep Convolutional Neural Network Based Segmentation and Two-Pass Contour Refinement.
Liu C; Pang M
J Digit Imaging; 2020 Dec; 33(6):1465-1478. PubMed ID: 33057882
[TBL] [Abstract][Full Text] [Related]
23. RPLS-Net: pulmonary lobe segmentation based on 3D fully convolutional networks and multi-task learning.
Liu J; Wang C; Guo J; Shao J; Xu X; Liu X; Li H; Li W; Yi Z
Int J Comput Assist Radiol Surg; 2021 Jun; 16(6):895-904. PubMed ID: 33846890
[TBL] [Abstract][Full Text] [Related]
24. UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation.
Hassan R; Mondal MRH; Ahamed SI
PLoS One; 2024; 19(6):e0304771. PubMed ID: 38885241
[TBL] [Abstract][Full Text] [Related]
25. A deep learning based dual encoder-decoder framework for anatomical structure segmentation in chest X-ray images.
Ullah I; Ali F; Shah B; El-Sappagh S; Abuhmed T; Park SH
Sci Rep; 2023 Jan; 13(1):791. PubMed ID: 36646735
[TBL] [Abstract][Full Text] [Related]
26. 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]
27. Lung Segmentation on HRCT and Volumetric CT for Diffuse Interstitial Lung Disease Using Deep Convolutional Neural Networks.
Park B; Park H; Lee SM; Seo JB; Kim N
J Digit Imaging; 2019 Dec; 32(6):1019-1026. PubMed ID: 31396776
[TBL] [Abstract][Full Text] [Related]
28. Automated Detection and Quantification of COVID-19 Airspace Disease on Chest Radiographs: A Novel Approach Achieving Expert Radiologist-Level Performance Using a Deep Convolutional Neural Network Trained on Digital Reconstructed Radiographs From Computed Tomography-Derived Ground Truth.
Mortani Barbosa EJ; Gefter WB; Ghesu FC; Liu S; Mailhe B; Mansoor A; Grbic S; Vogt S
Invest Radiol; 2021 Aug; 56(8):471-479. PubMed ID: 33481459
[TBL] [Abstract][Full Text] [Related]
29. A comprehensive segmentation of chest X-ray improves deep learning-based WHO radiologically confirmed pneumonia diagnosis in children.
Li Y; Zhang L; Yu H; Wang J; Wang S; Liu J; Zheng Q
Eur Radiol; 2024 May; 34(5):3471-3482. PubMed ID: 37930411
[TBL] [Abstract][Full Text] [Related]
30. Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.
Li D; Liu L; Chen J; Li H; Yin Y; Ibragimov B; Xing L
Phys Med Biol; 2017 Jan; 62(1):272-288. PubMed ID: 27991439
[TBL] [Abstract][Full Text] [Related]
31. Liver segmentation in abdominal CT images via auto-context neural network and self-supervised contour attention.
Chung M; Lee J; Park S; Lee CE; Lee J; Shin YG
Artif Intell Med; 2021 Mar; 113():102023. PubMed ID: 33685586
[TBL] [Abstract][Full Text] [Related]
32. Chest X-ray pneumothorax segmentation using U-Net with EfficientNet and ResNet architectures.
Abedalla A; Abdullah M; Al-Ayyoub M; Benkhelifa E
PeerJ Comput Sci; 2021; 7():e607. PubMed ID: 34307860
[TBL] [Abstract][Full Text] [Related]
33. CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.
Liu Z; Yuan H; Wang H
Med Phys; 2022 Aug; 49(8):5294-5303. PubMed ID: 35609213
[TBL] [Abstract][Full Text] [Related]
34. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.
Xu M; Qi S; Yue Y; Teng Y; Xu L; Yao Y; Qian W
Biomed Eng Online; 2019 Jan; 18(1):2. PubMed ID: 30602393
[TBL] [Abstract][Full Text] [Related]
35. Global optimal hybrid geometric active contour for automated lung segmentation on CT images.
Zhang W; Wang X; Zhang P; Chen J
Comput Biol Med; 2017 Dec; 91():168-180. PubMed ID: 29080491
[TBL] [Abstract][Full Text] [Related]
36. Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.
Hu P; Wu F; Peng J; Bao Y; Chen F; Kong D
Int J Comput Assist Radiol Surg; 2017 Mar; 12(3):399-411. PubMed ID: 27885540
[TBL] [Abstract][Full Text] [Related]
37. Automated vessel segmentation in lung CT and CTA images via deep neural networks.
Tan W; Zhou L; Li X; Yang X; Chen Y; Yang J
J Xray Sci Technol; 2021; 29(6):1123-1137. PubMed ID: 34421004
[TBL] [Abstract][Full Text] [Related]
38. Comparison of the automatic segmentation of multiple organs at risk in CT images of lung cancer between deep convolutional neural network-based and atlas-based techniques.
Zhu J; Zhang J; Qiu B; Liu Y; Liu X; Chen L
Acta Oncol; 2019 Feb; 58(2):257-264. PubMed ID: 30398090
[TBL] [Abstract][Full Text] [Related]
39. FAPNET: Feature Fusion with Adaptive Patch for Flood-Water Detection and Monitoring.
Islam MDS; Sun X; Wang Z; Cheng I
Sensors (Basel); 2022 Oct; 22(21):. PubMed ID: 36365943
[TBL] [Abstract][Full Text] [Related]
40. Weighing features of lung and heart regions for thoracic disease classification.
Fang J; Xu Y; Zhao Y; Yan Y; Liu J; Liu J
BMC Med Imaging; 2021 Jun; 21(1):99. PubMed ID: 34112095
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]