BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

272 related articles for article (PubMed ID: 36738608)

  • 1. PyRaDiSe: A Python package for DICOM-RT-based auto-segmentation pipeline construction and DICOM-RT data conversion.
    Rüfenacht E; Kamath A; Suter Y; Poel R; Ermiş E; Scheib S; Reyes M
    Comput Methods Programs Biomed; 2023 Apr; 231():107374. PubMed ID: 36738608
    [TBL] [Abstract][Full Text] [Related]  

  • 2. pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis.
    Jungo A; Scheidegger O; Reyes M; Balsiger F
    Comput Methods Programs Biomed; 2021 Jan; 198():105796. PubMed ID: 33137700
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Simple Python Module for Conversions Between DICOM Images and Radiation Therapy Structures, Masks, and Prediction Arrays.
    Anderson BM; Wahid KA; Brock KK
    Pract Radiat Oncol; 2021; 11(3):226-229. PubMed ID: 33607331
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A vendor-agnostic, PACS integrated, and DICOM-compatible software-server pipeline for testing segmentation algorithms within the clinical radiology workflow.
    Zhang L; LaBelle W; Unberath M; Chen H; Hu J; Li G; Dreizin D
    Front Med (Lausanne); 2023; 10():1241570. PubMed ID: 37954555
    [TBL] [Abstract][Full Text] [Related]  

  • 5. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
    Zhu W; Huang Y; Zeng L; Chen X; Liu Y; Qian Z; Du N; Fan W; Xie X
    Med Phys; 2019 Feb; 46(2):576-589. PubMed ID: 30480818
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer.
    Ahn SH; Yeo AU; Kim KH; Kim C; Goh Y; Cho S; Lee SB; Lim YK; Kim H; Shin D; Kim T; Kim TH; Youn SH; Oh ES; Jeong JH
    Radiat Oncol; 2019 Nov; 14(1):213. PubMed ID: 31775825
    [TBL] [Abstract][Full Text] [Related]  

  • 7. TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning.
    Pérez-García F; Sparks R; Ourselin S
    Comput Methods Programs Biomed; 2021 Sep; 208():106236. PubMed ID: 34311413
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT.
    Iyer A; Thor M; Onochie I; Hesse J; Zakeri K; LoCastro E; Jiang J; Veeraraghavan H; Elguindi S; Lee NY; Deasy JO; Apte AP
    Phys Med Biol; 2022 Jan; 67(2):. PubMed ID: 34874302
    [No Abstract]   [Full Text] [Related]  

  • 9. Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging.
    Korte JC; Hardcastle N; Ng SP; Clark B; Kron T; Jackson P
    Med Phys; 2021 Dec; 48(12):7757-7772. PubMed ID: 34676555
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning.
    Müller D; Kramer F
    BMC Med Imaging; 2021 Jan; 21(1):12. PubMed ID: 33461500
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer.
    Guo H; Wang J; Xia X; Zhong Y; Peng J; Zhang Z; Hu W
    Radiat Oncol; 2021 Jun; 16(1):113. PubMed ID: 34162410
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A vendor-agnostic, PACS integrated, and DICOMcompatible software-server pipeline for testing segmentation algorithms within the clinical radiology workflow.
    Zhang L; LaBelle W; Unberath M; Chen H; Hu J; Li G; Dreizin D
    Res Sq; 2023 Apr; ():. PubMed ID: 37163064
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery.
    Chung SY; Chang JS; Choi MS; Chang Y; Choi BS; Chun J; Keum KC; Kim JS; Kim YB
    Radiat Oncol; 2021 Feb; 16(1):44. PubMed ID: 33632248
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Technical Note: PYRO-NN: Python reconstruction operators in neural networks.
    Syben C; Michen M; Stimpel B; Seitz S; Ploner S; Maier AK
    Med Phys; 2019 Nov; 46(11):5110-5115. PubMed ID: 31389023
    [TBL] [Abstract][Full Text] [Related]  

  • 15. MIDGET:Detecting differential gene expression on microarray data.
    Angelescu R; Dobrescu R
    Comput Methods Programs Biomed; 2021 Nov; 211():106418. PubMed ID: 34555591
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Evaluating Automatic Segmentation for Swallowing-Related Organs for Head and Neck Cancer.
    Li Y; Rao S; Chen W; Azghadi SF; Nguyen KNB; Moran A; Usera BM; Dyer BA; Shang L; Chen Q; Rong Y
    Technol Cancer Res Treat; 2022; 21():15330338221105724. PubMed ID: 35790457
    [No Abstract]   [Full Text] [Related]  

  • 17. Auto-segmentation of important centers of growth in the pediatric skeleton to consider during radiation therapy based on deep learning.
    Qiu W; Zhang W; Ma X; Kong Y; Shi P; Fu M; Wang D; Hu M; Zhou X; Dong Q; Zhou Q; Zhu J
    Med Phys; 2023 Jan; 50(1):284-296. PubMed ID: 36047281
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MISeval: A Metric Library for Medical Image Segmentation Evaluation.
    Müller D; Hartmann D; Meyer P; Auer F; Soto-Rey I; Kramer F
    Stud Health Technol Inform; 2022 May; 294():33-37. PubMed ID: 35612011
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods.
    Vrtovec T; Močnik D; Strojan P; Pernuš F; Ibragimov B
    Med Phys; 2020 Sep; 47(9):e929-e950. PubMed ID: 32510603
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Enabling machine learning in X-ray-based procedures via realistic simulation of image formation.
    Unberath M; Zaech JN; Gao C; Bier B; Goldmann F; Lee SC; Fotouhi J; Taylor R; Armand M; Navab N
    Int J Comput Assist Radiol Surg; 2019 Sep; 14(9):1517-1528. PubMed ID: 31187399
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.