153 related articles for article (PubMed ID: 36097497)
1. A bi-directional deep learning architecture for lung nodule semantic segmentation.
Bhattacharyya D; Thirupathi Rao N; Joshua ESN; Hu YC
Vis Comput; 2022 Sep; ():1-17. PubMed ID: 36097497
[TBL] [Abstract][Full Text] [Related]
2. Hybrid U-Net-based deep learning model for volume segmentation of lung nodules in CT images.
Wang Y; Zhou C; Chan HP; Hadjiiski LM; Chughtai A; Kazerooni EA
Med Phys; 2022 Nov; 49(11):7287-7302. PubMed ID: 35717560
[TBL] [Abstract][Full Text] [Related]
3. A Bi-FPN-Based Encoder-Decoder Model for Lung Nodule Image Segmentation.
Annavarapu CSR; Parisapogu SAB; Keetha NV; Donta PK; Rajita G
Diagnostics (Basel); 2023 Apr; 13(8):. PubMed ID: 37189507
[TBL] [Abstract][Full Text] [Related]
4. Design of lung nodules segmentation and recognition algorithm based on deep learning.
Yu H; Li J; Zhang L; Cao Y; Yu X; Sun J
BMC Bioinformatics; 2021 Nov; 22(Suppl 5):314. PubMed ID: 34749636
[TBL] [Abstract][Full Text] [Related]
5. Boundary Aware Semantic Segmentation using Pyramid-dilated Dense U-Net for Lung Segmentation in Computed Tomography Images.
Agnes SA
J Med Phys; 2023; 48(2):161-174. PubMed ID: 37576094
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Construction of U-Net++ pulmonary nodule intelligent analysis model based on feature weighted aggregation.
Yang D; Du J; Liu K; Sui Y; Wang J; Gai X
Technol Health Care; 2023; 31(S1):477-486. PubMed ID: 37066943
[TBL] [Abstract][Full Text] [Related]
8. Computed Tomography Image under Convolutional Neural Network Deep Learning Algorithm in Pulmonary Nodule Detection and Lung Function Examination.
Zhang C; Li J; Huang J; Wu S
J Healthc Eng; 2021; 2021():3417285. PubMed ID: 34721823
[TBL] [Abstract][Full Text] [Related]
9. RAD-UNet: Research on an improved lung nodule semantic segmentation algorithm based on deep learning.
Wu Z; Li X; Zuo J
Front Oncol; 2023; 13():1084096. PubMed ID: 37035155
[TBL] [Abstract][Full Text] [Related]
10. Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.
Dong X; Xu S; Liu Y; Wang A; Saripan MI; Li L; Zhang X; Lu L
Cancer Imaging; 2020 Aug; 20(1):53. PubMed ID: 32738913
[TBL] [Abstract][Full Text] [Related]
11. Appraisal of Deep-Learning Techniques on Computer-Aided Lung Cancer Diagnosis with Computed Tomography Screening.
Agnes SA; Anitha J
J Med Phys; 2020; 45(2):98-106. PubMed ID: 32831492
[TBL] [Abstract][Full Text] [Related]
12. Automatic detection of lung nodules in CT datasets based on stable 3D mass-spring models.
Cascio D; Magro R; Fauci F; Iacomi M; Raso G
Comput Biol Med; 2012 Nov; 42(11):1098-109. PubMed ID: 23020972
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Two-stage multitask U-Net construction for pulmonary nodule segmentation and malignancy risk prediction.
Ni Y; Xie Z; Zheng D; Yang Y; Wang W
Quant Imaging Med Surg; 2022 Jan; 12(1):292-309. PubMed ID: 34993079
[TBL] [Abstract][Full Text] [Related]
15. Two-stage lung nodule detection framework using enhanced UNet and convolutional LSTM networks in CT images.
Akila Agnes S; Anitha J; Arun Solomon A
Comput Biol Med; 2022 Oct; 149():106059. PubMed ID: 36087510
[TBL] [Abstract][Full Text] [Related]
16. TPFR-Net: U-shaped model for lung nodule segmentation based on transformer pooling and dual-attention feature reorganization.
Li X; Jiang A; Qiu Y; Li M; Zhang X; Yan S
Med Biol Eng Comput; 2023 Aug; 61(8):1929-1946. PubMed ID: 37243853
[TBL] [Abstract][Full Text] [Related]
17. A cascaded dual-pathway residual network for lung nodule segmentation in CT images.
Liu H; Cao H; Song E; Ma G; Xu X; Jin R; Jin Y; Hung CC
Phys Med; 2019 Jul; 63():112-121. PubMed ID: 31221402
[TBL] [Abstract][Full Text] [Related]
18. Segmentation of thyroid glands and nodules in ultrasound images using the improved U-Net architecture.
Zheng T; Qin H; Cui Y; Wang R; Zhao W; Zhang S; Geng S; Zhao L
BMC Med Imaging; 2023 Apr; 23(1):56. PubMed ID: 37060061
[TBL] [Abstract][Full Text] [Related]
19. Segmentation of Lung Nodules on CT Images Using a Nested Three-Dimensional Fully Connected Convolutional Network.
Kido S; Kidera S; Hirano Y; Mabu S; Kamiya T; Tanaka N; Suzuki Y; Yanagawa M; Tomiyama N
Front Artif Intell; 2022; 5():782225. PubMed ID: 35252849
[TBL] [Abstract][Full Text] [Related]
20. Conventional Filtering Versus U-Net Based Models for Pulmonary Nodule Segmentation in CT Images.
Rocha J; Cunha A; Mendonça AM
J Med Syst; 2020 Mar; 44(4):81. PubMed ID: 32140870
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
