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 *

116 related articles for article (PubMed ID: 24386531)

  • 41. Robust brain ROI segmentation by deformation regression and deformable shape model.
    Wu Z; Guo Y; Park SH; Gao Y; Dong P; Lee SW; Shen D
    Med Image Anal; 2018 Jan; 43():198-213. PubMed ID: 29149715
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Tumor segmentation from computed tomography image data using a probabilistic pixel selection approach.
    Foo JL; Miyano G; Lobe T; Winer E
    Comput Biol Med; 2011 Jan; 41(1):56-65. PubMed ID: 21146165
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Automatic liver segmentation by integrating fully convolutional networks into active contour models.
    Guo X; Schwartz LH; Zhao B
    Med Phys; 2019 Oct; 46(10):4455-4469. PubMed ID: 31356688
    [TBL] [Abstract][Full Text] [Related]  

  • 44. A new osteophyte segmentation algorithm using partial shape model and its applications to rabbit femur anterior cruciate ligament transection via micro-CT imaging.
    Saha PK; Liang G; Elkins JM; Coimbra A; Duong LT; Williams DS; Sonka M
    IEEE Trans Biomed Eng; 2011 Aug; 58(8):. PubMed ID: 21421428
    [TBL] [Abstract][Full Text] [Related]  

  • 45. A modified level set algorithm based on point distance shape constraint for lesion and organ segmentation.
    Li X; Li C; Liu H; Yang X
    Phys Med; 2019 Jan; 57():123-136. PubMed ID: 30738516
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Medial axis segmentation of cranial nerves using shape statistics-aware discrete deformable models.
    Sultana S; Agrawal P; Elhabian S; Whitaker R; Blatt JE; Gilles B; Cetas J; Rashid T; Audette MA
    Int J Comput Assist Radiol Surg; 2019 Nov; 14(11):1955-1967. PubMed ID: 31236805
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Model-based segmentation of the middle phalanx in digital radiographic images of the hand.
    Dendere R; Kabelitz G; Douglas TS
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():3702-5. PubMed ID: 24110534
    [TBL] [Abstract][Full Text] [Related]  

  • 48. An adaptive motion regularization technique to support sliding motion in deformable image registration.
    Fu Y; Liu S; Li HH; Li H; Yang D
    Med Phys; 2018 Feb; 45(2):735-747. PubMed ID: 29251777
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.
    Ciller C; De Zanet SI; Rüegsegger MB; Pica A; Sznitman R; Thiran JP; Maeder P; Munier FL; Kowal JH; Cuadra MB
    Int J Radiat Oncol Biol Phys; 2015 Jul; 92(4):794-802. PubMed ID: 26104933
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model.
    Martin S; Troccaz J; Daanenc V
    Med Phys; 2010 Apr; 37(4):1579-90. PubMed ID: 20443479
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Parametric shape modeling using deformable superellipses for prostate segmentation.
    Gong L; Pathak SD; Haynor DR; Cho PS; Kim Y
    IEEE Trans Med Imaging; 2004 Mar; 23(3):340-9. PubMed ID: 15027527
    [TBL] [Abstract][Full Text] [Related]  

  • 52. A deformable-model approach to semi-automatic segmentation of CT images demonstrated by application to the spinal canal.
    Burnett SS; Starkschalla G; Stevens CW; Liao Z
    Med Phys; 2004 Feb; 31(2):251-63. PubMed ID: 15000611
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Cascaded statistical shape model based segmentation of the full lower limb in CT.
    Audenaert EA; Van Houcke J; Almeida DF; Paelinck L; Peiffer M; Steenackers G; Vandermeulen D
    Comput Methods Biomech Biomed Engin; 2019 May; 22(6):644-657. PubMed ID: 30822149
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Active shape model registration of ocular structures in computed tomography images.
    Liu Y; Ota M; Han R; Siewerdsen JH; Liu TYA; Jones CK
    Phys Med Biol; 2022 Nov; 67(22):. PubMed ID: 36240761
    [No Abstract]   [Full Text] [Related]  

  • 55. Multi-object active shape model construction for abdomen segmentation: preliminary results.
    Gollmer ST; Simon M; Bischof A; Barkhausen J; Buzug TM
    Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():3990-3. PubMed ID: 23366802
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Whole Abdominal Wall Segmentation using Augmented Active Shape Models (AASM) with Multi-Atlas Label Fusion and Level Set.
    Xu Z; Baucom RB; Abramson RG; Poulose BK; Landman BA
    Proc SPIE Int Soc Opt Eng; 2016 Feb; 9784():. PubMed ID: 27127333
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Shape-intensity prior level set combining probabilistic atlas and probability map constrains for automatic liver segmentation from abdominal CT images.
    Wang J; Cheng Y; Guo C; Wang Y; Tamura S
    Int J Comput Assist Radiol Surg; 2016 May; 11(5):817-26. PubMed ID: 26646416
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Automatic liver segmentation using 3D convolutional neural networks with a hybrid loss function.
    Tan M; Wu F; Kong D; Mao X
    Med Phys; 2021 Apr; 48(4):1707-1719. PubMed ID: 33496971
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.
    de Bruijne M; van Ginneken B; Viergever MA; Niessen WJ
    Inf Process Med Imaging; 2003 Jul; 18():136-47. PubMed ID: 15344453
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Automated segmentation for patella from lateral knee X-ray images.
    Chen HC; Wu CH; Lin CJ; Liu YH; Sun YN
    Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():3553-6. PubMed ID: 19963588
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.