124 related articles for article (PubMed ID: 37201475)
21. Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.
Ye LY; Miao XY; Cai WS; Xu WJ
Comput Methods Programs Biomed; 2022 Jun; 221():106770. PubMed ID: 35640389
[TBL] [Abstract][Full Text] [Related]
22. Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy.
Savenije MHF; Maspero M; Sikkes GG; van der Voort van Zyp JRN; T J Kotte AN; Bol GH; T van den Berg CA
Radiat Oncol; 2020 May; 15(1):104. PubMed ID: 32393280
[TBL] [Abstract][Full Text] [Related]
23. CAN3D: Fast 3D medical image segmentation via compact context aggregation.
Dai W; Woo B; Liu S; Marques M; Engstrom C; Greer PB; Crozier S; Dowling JA; Chandra SS
Med Image Anal; 2022 Nov; 82():102562. PubMed ID: 36049450
[TBL] [Abstract][Full Text] [Related]
24. Lung tumor segmentation in 4D CT images using motion convolutional neural networks.
Momin S; Lei Y; Tian Z; Wang T; Roper J; Kesarwala AH; Higgins K; Bradley JD; Liu T; Yang X
Med Phys; 2021 Nov; 48(11):7141-7153. PubMed ID: 34469001
[TBL] [Abstract][Full Text] [Related]
25. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.
Guo Y; Gao Y; Shao Y; Price T; Oto A; Shen D
Med Phys; 2014 Jul; 41(7):072303. PubMed ID: 24989402
[TBL] [Abstract][Full Text] [Related]
26. PSA-Net: Deep learning-based physician style-aware segmentation network for postoperative prostate cancer clinical target volumes.
Balagopal A; Morgan H; Dohopolski M; Timmerman R; Shan J; Heitjan DF; Liu W; Nguyen D; Hannan R; Garant A; Desai N; Jiang S
Artif Intell Med; 2021 Nov; 121():102195. PubMed ID: 34763810
[TBL] [Abstract][Full Text] [Related]
27. Learning image context for segmentation of the prostate in CT-guided radiotherapy.
Li W; Liao S; Feng Q; Chen W; Shen D
Phys Med Biol; 2012 Mar; 57(5):1283-308. PubMed ID: 22343071
[TBL] [Abstract][Full Text] [Related]
28. Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net.
Aldoj N; Biavati F; Michallek F; Stober S; Dewey M
Sci Rep; 2020 Aug; 10(1):14315. PubMed ID: 32868836
[TBL] [Abstract][Full Text] [Related]
29. Multi-eXpert fusion: An ensemble learning framework to segment 3D TRUS prostate images.
Beitone C; Troccaz J
Med Phys; 2022 Aug; 49(8):5138-5148. PubMed ID: 35443086
[TBL] [Abstract][Full Text] [Related]
30. Fully automated segmentation of prostatic urethra for MR-guided radiation therapy.
Xu D; Ma TM; Savjani R; Pham J; Cao M; Yang Y; Kishan AU; Scalzo F; Sheng K
Med Phys; 2023 Jan; 50(1):354-364. PubMed ID: 36106703
[TBL] [Abstract][Full Text] [Related]
31. ARPM-net: A novel CNN-based adversarial method with Markov random field enhancement for prostate and organs at risk segmentation in pelvic CT images.
Zhang Z; Zhao T; Gay H; Zhang W; Sun B
Med Phys; 2021 Jan; 48(1):227-237. PubMed ID: 33151620
[TBL] [Abstract][Full Text] [Related]
32. Pelvic Organ Segmentation Using Distinctive Curve Guided Fully Convolutional Networks.
He K; Cao X; Shi Y; Nie D; Gao Y; Shen D
IEEE Trans Med Imaging; 2019 Feb; 38(2):585-595. PubMed ID: 30176583
[TBL] [Abstract][Full Text] [Related]
33. Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI.
Khan Z; Yahya N; Alsaih K; Ali SSA; Meriaudeau F
Sensors (Basel); 2020 Jun; 20(11):. PubMed ID: 32503330
[TBL] [Abstract][Full Text] [Related]
34. Automated segmentation of prostate zonal anatomy on T2-weighted (T2W) and apparent diffusion coefficient (ADC) map MR images using U-Nets.
Zabihollahy F; Schieda N; Krishna Jeyaraj S; Ukwatta E
Med Phys; 2019 Jul; 46(7):3078-3090. PubMed ID: 31002381
[TBL] [Abstract][Full Text] [Related]
35. Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss.
Xu Y; Klyuzhin I; Harsini S; Ortiz A; Zhang S; BĂ©nard F; Dodhia R; Uribe CF; Rahmim A; Lavista Ferres J
Comput Biol Med; 2023 May; 158():106882. PubMed ID: 37037147
[TBL] [Abstract][Full Text] [Related]
36. Prostate lesion segmentation based on a 3D end-to-end convolution neural network with deep multi-scale attention.
Song E; Long J; Ma G; Liu H; Hung CC; Jin R; Wang P; Wang W
Magn Reson Imaging; 2023 Jun; 99():98-109. PubMed ID: 36681311
[TBL] [Abstract][Full Text] [Related]
37. ParaCM-PNet: A CNN-tokenized MLP combined parallel dual pyramid network for prostate and prostate cancer segmentation in MRI.
Wang W; Pan B; Ai Y; Li G; Fu Y; Liu Y
Comput Biol Med; 2024 Mar; 170():107999. PubMed ID: 38244470
[TBL] [Abstract][Full Text] [Related]
38. MR to ultrasound image registration with segmentation-based learning for HDR prostate brachytherapy.
Chen Y; Xing L; Yu L; Liu W; Pooya Fahimian B; Niedermayr T; Bagshaw HP; Buyyounouski M; Han B
Med Phys; 2021 Jun; 48(6):3074-3083. PubMed ID: 33905566
[TBL] [Abstract][Full Text] [Related]
39. Accuracy Validation of an Automated Method for Prostate Segmentation in Magnetic Resonance Imaging.
Shahedi M; Cool DW; Bauman GS; Bastian-Jordan M; Fenster A; Ward AD
J Digit Imaging; 2017 Dec; 30(6):782-795. PubMed ID: 28342043
[TBL] [Abstract][Full Text] [Related]
40. HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation in CT Images.
He K; Lian C; Zhang B; Zhang X; Cao X; Nie D; Gao Y; Zhang J; Shen D
IEEE Trans Med Imaging; 2021 Aug; 40(8):2118-2128. PubMed ID: 33848243
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]