148 related articles for article (PubMed ID: 31529237)
21. Segmenting brain tumors from FLAIR MRI using fully convolutional neural networks.
Ribalta Lorenzo P; Nalepa J; Bobek-Billewicz B; Wawrzyniak P; Mrukwa G; Kawulok M; Ulrych P; Hayball MP
Comput Methods Programs Biomed; 2019 Jul; 176():135-148. PubMed ID: 31200901
[TBL] [Abstract][Full Text] [Related]
22. A novel fully automatic multilevel thresholding technique based on optimized intuitionistic fuzzy sets and tsallis entropy for MR brain tumor image segmentation.
Kaur T; Saini BS; Gupta S
Australas Phys Eng Sci Med; 2018 Mar; 41(1):41-58. PubMed ID: 29238919
[TBL] [Abstract][Full Text] [Related]
23. Brain Tumor Detection and Segmentation by Intensity Adjustment.
Rajan PG; Sundar C
J Med Syst; 2019 Jul; 43(8):282. PubMed ID: 31300899
[TBL] [Abstract][Full Text] [Related]
24. Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy.
Ben Naceur M; Akil M; Saouli R; Kachouri R
Med Image Anal; 2020 Jul; 63():101692. PubMed ID: 32417714
[TBL] [Abstract][Full Text] [Related]
25. A knowledge-based system for brain tumor segmentation using only 3D FLAIR images.
Amirmoezzi Y; Salehi S; Parsaei H; Kazemi K; Torabi Jahromi A
Australas Phys Eng Sci Med; 2019 Jun; 42(2):529-540. PubMed ID: 30963459
[TBL] [Abstract][Full Text] [Related]
26. MRI Brain Images Classification: A Multi-Level Threshold Based Region Optimization Technique.
Kanmani P; Marikkannu P
J Med Syst; 2018 Feb; 42(4):62. PubMed ID: 29479647
[TBL] [Abstract][Full Text] [Related]
27. Segmentation of white blood cells and comparison of cell morphology by linear and naïve Bayes classifiers.
Prinyakupt J; Pluempitiwiriyawej C
Biomed Eng Online; 2015 Jun; 14():63. PubMed ID: 26123131
[TBL] [Abstract][Full Text] [Related]
28. Fast and robust brain tumor segmentation using level set method with multiple image information.
Lok KH; Shi L; Zhu X; Wang D
J Xray Sci Technol; 2017; 25(2):301-312. PubMed ID: 28269819
[TBL] [Abstract][Full Text] [Related]
29. A new deformable model based on fractional Wright energy function for tumor segmentation of volumetric brain MRI scans.
Ibrahim RW; Hasan AM; Jalab HA
Comput Methods Programs Biomed; 2018 Sep; 163():21-28. PubMed ID: 30119853
[TBL] [Abstract][Full Text] [Related]
30. Robust spatial fuzzy GMM based MRI segmentation and carotid artery plaque detection in ultrasound images.
Hassan M; Murtza I; Hira A; Ali S; Kifayat K
Comput Methods Programs Biomed; 2019 Jul; 175():179-192. PubMed ID: 31104706
[TBL] [Abstract][Full Text] [Related]
31. Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.
Sauwen N; Acou M; Sima DM; Veraart J; Maes F; Himmelreich U; Achten E; Huffel SV
BMC Med Imaging; 2017 May; 17(1):29. PubMed ID: 28472943
[TBL] [Abstract][Full Text] [Related]
32. An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation.
Hoseini F; Shahbahrami A; Bayat P
J Digit Imaging; 2018 Oct; 31(5):738-747. PubMed ID: 29488179
[TBL] [Abstract][Full Text] [Related]
33. 3D cerebral MR image segmentation using multiple-classifier system.
Amiri S; Movahedi MM; Kazemi K; Parsaei H
Med Biol Eng Comput; 2017 Mar; 55(3):353-364. PubMed ID: 27207464
[TBL] [Abstract][Full Text] [Related]
34. On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.
Sengupta A; Agarwal S; Gupta PK; Ahlawat S; Patir R; Gupta RK; Singh A
Eur J Radiol; 2018 Sep; 106():199-208. PubMed ID: 30150045
[TBL] [Abstract][Full Text] [Related]
35. Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.
Dolz J; Laprie A; Ken S; Leroy HA; Reyns N; Massoptier L; Vermandel M
Int J Comput Assist Radiol Surg; 2016 Jan; 11(1):43-51. PubMed ID: 26206715
[TBL] [Abstract][Full Text] [Related]
36. Fast level set method for glioma brain tumor segmentation based on Superpixel fuzzy clustering and lattice Boltzmann method.
Khosravanian A; Rahmanimanesh M; Keshavarzi P; Mozaffari S
Comput Methods Programs Biomed; 2021 Jan; 198():105809. PubMed ID: 33130495
[TBL] [Abstract][Full Text] [Related]
37. An Enhancement of Deep Learning Algorithm for Brain Tumor Segmentation Using Kernel Based CNN with M-SVM.
Thillaikkarasi R; Saravanan S
J Med Syst; 2019 Feb; 43(4):84. PubMed ID: 30810822
[TBL] [Abstract][Full Text] [Related]
38. Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.
Altazi BA; Zhang GG; Fernandez DC; Montejo ME; Hunt D; Werner J; Biagioli MC; Moros EG
J Appl Clin Med Phys; 2017 Nov; 18(6):32-48. PubMed ID: 28891217
[TBL] [Abstract][Full Text] [Related]
39. Automatic selection of localized region-based active contour models using image content analysis applied to brain tumor segmentation.
Ilunga-Mbuyamba E; Avina-Cervantes JG; Cepeda-Negrete J; Ibarra-Manzano MA; Chalopin C
Comput Biol Med; 2017 Dec; 91():69-79. PubMed ID: 29049909
[TBL] [Abstract][Full Text] [Related]
40. An unsupervised automatic segmentation algorithm for breast tissue classification of dedicated breast computed tomography images.
Caballo M; Boone JM; Mann R; Sechopoulos I
Med Phys; 2018 Jun; 45(6):2542-2559. PubMed ID: 29676025
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
