These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

155 related articles for article (PubMed ID: 36744695)

  • 21. Towards the definition of a patient-specific rehabilitation program for TKA: A new MRI-based approach for the easy volumetric analysis of thigh muscles
    Azimbagirad M; Dardenne G; Salem DB; Remy-Neris O; Burdin V
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3141-3144. PubMed ID: 34891907
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Deep Learning-Based Fully Automated Segmentation of Regional Muscle Volume and Spatial Intermuscular Fat Using CT.
    Zhang R; He A; Xia W; Su Y; Jian J; Liu Y; Guo Z; Shi W; Zhang Z; He B; Cheng X; Gao X; Liu Y; Wang L
    Acad Radiol; 2023 Oct; 30(10):2280-2289. PubMed ID: 37429780
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Deep network and multi-atlas segmentation fusion for delineation of thigh muscle groups in three-dimensional water-fat separated MRI.
    Annasamudram NV; Okorie AM; Spencer RG; Kalyani RR; Yang Q; Landman BA; Ferrucci L; Makrogiannis S
    J Med Imaging (Bellingham); 2024 Sep; 11(5):054003. PubMed ID: 39234425
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping.
    Ghadimi S; Auger DA; Feng X; Sun C; Meyer CH; Bilchick KC; Cao JJ; Scott AD; Oshinski JN; Ennis DB; Epstein FH
    J Cardiovasc Magn Reson; 2021 Mar; 23(1):20. PubMed ID: 33691739
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Automatic MRI-based Three-dimensional Models of Hip Cartilage Provide Improved Morphologic and Biochemical Analysis.
    Schmaranzer F; Helfenstein R; Zeng G; Lerch TD; Novais EN; Wylie JD; Kim YJ; Siebenrock KA; Tannast M; Zheng G
    Clin Orthop Relat Res; 2019 May; 477(5):1036-1052. PubMed ID: 30998632
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.
    Chen Y; Xing L; Yu L; Bagshaw HP; Buyyounouski MK; Han B
    Med Phys; 2020 Dec; 47(12):6421-6429. PubMed ID: 33012016
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Novel stochastic framework for automatic segmentation of human thigh MRI volumes and its applications in spinal cord injured individuals.
    Mesbah S; Shalaby AM; Stills S; Soliman AM; Willhite A; Harkema SJ; Rejc E; El-Baz AS
    PLoS One; 2019; 14(5):e0216487. PubMed ID: 31071158
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Deep learning-based automated segmentation of resection cavities on postsurgical epilepsy MRI.
    Arnold TC; Muthukrishnan R; Pattnaik AR; Sinha N; Gibson A; Gonzalez H; Das SR; Litt B; Englot DJ; Morgan VL; Davis KA; Stein JM
    Neuroimage Clin; 2022; 36():103154. PubMed ID: 35988342
    [TBL] [Abstract][Full Text] [Related]  

  • 29. A deep learning pipeline for automatic analysis of multi-scan cardiovascular magnetic resonance.
    Fadil H; Totman JJ; Hausenloy DJ; Ho HH; Joseph P; Low AF; Richards AM; Chan MY; Marchesseau S
    J Cardiovasc Magn Reson; 2021 Apr; 23(1):47. PubMed ID: 33896419
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry.
    Norman B; Pedoia V; Majumdar S
    Radiology; 2018 Jul; 288(1):177-185. PubMed ID: 29584598
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Quantification of Intra-Muscular Adipose Infiltration in Calf/Thigh MRI Using Fully and Weakly Supervised Semantic Segmentation.
    Amer R; Nassar J; Trabelsi A; Bendahan D; Greenspan H; Ben-Eliezer N
    Bioengineering (Basel); 2022 Jul; 9(7):. PubMed ID: 35877366
    [No Abstract]   [Full Text] [Related]  

  • 32. Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.
    Zhang L; Mohamed AA; Chai R; Guo Y; Zheng B; Wu S
    J Magn Reson Imaging; 2020 Feb; 51(2):635-643. PubMed ID: 31301201
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Positional contrastive learning for improved thigh muscle segmentation in MR images.
    Casali N; Scalco E; Taccogna MG; Lauretani F; Porcelli S; Ciuni A; Mastropietro A; Rizzo G
    NMR Biomed; 2024 Oct; 37(10):e5197. PubMed ID: 38822595
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.
    Qin W; Wu Y; Li S; Chen Y; Yang Y; Liu X; Zheng H; Liang D; Hu Z
    Biomed Phys Eng Express; 2020 Feb; 6(2):025009. PubMed ID: 33438635
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Automatic segmentation model of intercondylar fossa based on deep learning: a novel and effective assessment method for the notch volume.
    Li M; Bai H; Zhang F; Zhou Y; Lin Q; Zhou Q; Feng Q; Zhang L
    BMC Musculoskelet Disord; 2022 May; 23(1):426. PubMed ID: 35524293
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Development of an initial training and evaluation programme for manual lower limb muscle MRI segmentation.
    Morrow JM; Shah S; Cristiano L; Evans MRB; Doherty CM; Alnaemi T; Saab A; Emira A; Klickovic U; Hammam A; Altuwaijri A; Wastling S; Reilly MM; Hanna MG; Yousry TA; Thornton JS
    Eur Radiol Exp; 2024 Jul; 8(1):85. PubMed ID: 39060637
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Congenital diaphragmatic hernia: automatic lung and liver MRI segmentation with nnU-Net, reproducibility of pyradiomics features, and a machine learning application for the classification of liver herniation.
    Conte L; Amodeo I; De Nunzio G; Raffaeli G; Borzani I; Persico N; Griggio A; Como G; Cascio D; Colnaghi M; Mosca F; Cavallaro G
    Eur J Pediatr; 2024 May; 183(5):2285-2300. PubMed ID: 38416256
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Computerized Characterization of Spinal Structures on MRI and Clinical Significance of 3D Reconstruction of Lumbosacral Intervertebral Foramen.
    Liu Z; Su Z; Wang M; Chen T; Cui Z; Chen X; Li S; Feng Q; Pang S; Lu H
    Pain Physician; 2022 Jan; 25(1):E27-E35. PubMed ID: 35051149
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Validity and reliability of masseter muscles segmentation from the transverse sections of Cone-Beam CT scans compared with MRI scans.
    Pan Y; Wang Y; Li G; Chen S; Xu T
    Int J Comput Assist Radiol Surg; 2022 Apr; 17(4):751-759. PubMed ID: 34625872
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Automatic segmentation of the interscapular brown adipose tissue in rats based on deep learning using the dynamic magnetic resonance fat fraction images.
    Cheng C; Wu B; Zhang L; Wan Q; Peng H; Liu X; Zheng H; Zhang H; Zou C
    MAGMA; 2024 Apr; 37(2):215-226. PubMed ID: 38019377
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.