384 related articles for article (PubMed ID: 30465543)
1. Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features.
Macomber MW; Phillips M; Tarapov I; Jena R; Nori A; Carter D; Folgoc LL; Criminisi A; Nyflot MJ
Phys Med Biol; 2018 Nov; 63(23):235002. PubMed ID: 30465543
[TBL] [Abstract][Full Text] [Related]
2. Evaluation of a commercial DIR platform for contour propagation in prostate cancer patients treated with IMRT/VMAT.
Hammers JE; Pirozzi S; Lindsay D; Kaidar-Person O; Tan X; Chen RC; Das SK; Mavroidis P
J Appl Clin Med Phys; 2020 Feb; 21(2):14-25. PubMed ID: 32058663
[TBL] [Abstract][Full Text] [Related]
3. Evaluating the clinical acceptability of deep learning contours of prostate and organs-at-risk in an automated prostate treatment planning process.
Duan J; Bernard M; Downes L; Willows B; Feng X; Mourad WF; St Clair W; Chen Q
Med Phys; 2022 Apr; 49(4):2570-2581. PubMed ID: 35147216
[TBL] [Abstract][Full Text] [Related]
4. Technology assessment of automated atlas based segmentation in prostate bed contouring.
Hwee J; Louie AV; Gaede S; Bauman G; D'Souza D; Sexton T; Lock M; Ahmad B; Rodrigues G
Radiat Oncol; 2011 Sep; 6():110. PubMed ID: 21906279
[TBL] [Abstract][Full Text] [Related]
5. Assessment of accuracy and efficiency of atlas-based autosegmentation for prostate radiotherapy in a variety of clinical conditions.
Simmat I; Georg P; Georg D; Birkfellner W; Goldner G; Stock M
Strahlenther Onkol; 2012 Sep; 188(9):807-15. PubMed ID: 22669393
[TBL] [Abstract][Full Text] [Related]
6. Assessment of CT to CBCT contour mapping for radiomic feature analysis in prostate cancer.
Schmidt RM; Delgadillo R; Ford JC; Padgett KR; Studenski M; Abramowitz MC; Spieler B; Xu Y; Yang F; Dogan N
Sci Rep; 2021 Nov; 11(1):22737. PubMed ID: 34815464
[TBL] [Abstract][Full Text] [Related]
7. Evaluation and optimization of the parameters used in multiple-atlas-based segmentation of prostate cancers in radiation therapy.
Wong WK; Leung LH; Kwong DL
Br J Radiol; 2016; 89(1057):20140732. PubMed ID: 26539630
[TBL] [Abstract][Full Text] [Related]
8. An uncertainty-aware deep learning architecture with outlier mitigation for prostate gland segmentation in radiotherapy treatment planning.
Li X; Bagher-Ebadian H; Gardner S; Kim J; Elshaikh M; Movsas B; Zhu D; Chetty IJ
Med Phys; 2023 Jan; 50(1):311-322. PubMed ID: 36112996
[TBL] [Abstract][Full Text] [Related]
9. Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.
Kawula M; Hadi I; Nierer L; Vagni M; Cusumano D; Boldrini L; Placidi L; Corradini S; Belka C; Landry G; Kurz C
Med Phys; 2023 Mar; 50(3):1573-1585. PubMed ID: 36259384
[TBL] [Abstract][Full Text] [Related]
10. An atlas-based electron density mapping method for magnetic resonance imaging (MRI)-alone treatment planning and adaptive MRI-based prostate radiation therapy.
Dowling JA; Lambert J; Parker J; Salvado O; Fripp J; Capp A; Wratten C; Denham JW; Greer PB
Int J Radiat Oncol Biol Phys; 2012 May; 83(1):e5-11. PubMed ID: 22330995
[TBL] [Abstract][Full Text] [Related]
11. Impact of CT reconstruction algorithm on auto-segmentation performance.
Miller C; Mittelstaedt D; Black N; Klahr P; Nejad-Davarani S; Schulz H; Goshen L; Han X; Ghanem AI; Morris ED; Glide-Hurst C
J Appl Clin Med Phys; 2019 Sep; 20(9):95-103. PubMed ID: 31538718
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. A pair of deep learning auto-contouring models for prostate cancer patients injected with a radio-transparent versus radiopaque hydrogel spacer.
Wang Y; Boyd G; Zieminski S; Kamran SC; Zietman AL; Miyamoto DT; Kirk MC; Efstathiou JA
Med Phys; 2023 Jun; 50(6):3324-3337. PubMed ID: 36940384
[TBL] [Abstract][Full Text] [Related]
14. Multi-institutional quantitative evaluation and clinical validation of Smart Probabilistic Image Contouring Engine (SPICE) autosegmentation of target structures and normal tissues on computer tomography images in the head and neck, thorax, liver, and male pelvis areas.
Zhu M; Bzdusek K; Brink C; Eriksen JG; Hansen O; Jensen HA; Gay HA; Thorstad W; Widder J; Brouwer CL; Steenbakkers RJ; Vanhauten HA; Cao JQ; McBrayne G; Patel SH; Cannon DM; Hardcastle N; Tomé WA; Guckenberg M; Parikh PJ
Int J Radiat Oncol Biol Phys; 2013 Nov; 87(4):809-16. PubMed ID: 24138920
[TBL] [Abstract][Full Text] [Related]
15. Usefulness of hybrid deformable image registration algorithms in prostate radiation therapy.
Motegi K; Tachibana H; Motegi A; Hotta K; Baba H; Akimoto T
J Appl Clin Med Phys; 2019 Jan; 20(1):229-236. PubMed ID: 30592137
[TBL] [Abstract][Full Text] [Related]
16. Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.
Elmahdy MS; Jagt T; Zinkstok RT; Qiao Y; Shahzad R; Sokooti H; Yousefi S; Incrocci L; Marijnen CAM; Hoogeman M; Staring M
Med Phys; 2019 Aug; 46(8):3329-3343. PubMed ID: 31111962
[TBL] [Abstract][Full Text] [Related]
17. Pretreatment information-aided automatic segmentation for online magnetic resonance imaging-guided prostate radiotherapy.
Yang B; Liu Y; Zhu J; Lu N; Dai J; Men K
Med Phys; 2024 Feb; 51(2):922-932. PubMed ID: 37449545
[TBL] [Abstract][Full Text] [Related]
18. Deformable image registration for contour propagation from CT to cone-beam CT scans in radiotherapy of prostate cancer.
Thor M; Petersen JB; Bentzen L; Høyer M; Muren LP
Acta Oncol; 2011 Aug; 50(6):918-25. PubMed ID: 21767192
[TBL] [Abstract][Full Text] [Related]
19. Multi-observer contouring of male pelvic anatomy: Highly variable agreement across conventional and emerging structures of interest.
Roach D; Holloway LC; Jameson MG; Dowling JA; Kennedy A; Greer PB; Krawiec M; Rai R; Denham J; De Leon J; Lim K; Berry ME; White RT; Bydder SA; Tan HT; Croker JD; McGrath A; Matthews J; Smeenk RJ; Ebert MA
J Med Imaging Radiat Oncol; 2019 Apr; 63(2):264-271. PubMed ID: 30609205
[TBL] [Abstract][Full Text] [Related]
20. Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers.
Wong J; Huang V; Wells D; Giambattista J; Giambattista J; Kolbeck C; Otto K; Saibishkumar EP; Alexander A
Radiat Oncol; 2021 Jun; 16(1):101. PubMed ID: 34103062
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
