150 related articles for article (PubMed ID: 31529237)
1. Three-Phase Automatic Brain Tumor Diagnosis System Using Patches Based Updated Run Length Region Growing Technique.
Kalaiselvi T; Kumarashankar P; Sriramakrishnan P
J Digit Imaging; 2020 Apr; 33(2):465-479. PubMed ID: 31529237
[TBL] [Abstract][Full Text] [Related]
2. Fully automated segmentation of brain tumor from multiparametric MRI using 3D context deep supervised U-Net.
Lin M; Momin S; Lei Y; Wang H; Curran WJ; Liu T; Yang X
Med Phys; 2021 Aug; 48(8):4365-4374. PubMed ID: 34101845
[TBL] [Abstract][Full Text] [Related]
3. Comparative Approach of MRI-Based Brain Tumor Segmentation and Classification Using Genetic Algorithm.
Bahadure NB; Ray AK; Thethi HP
J Digit Imaging; 2018 Aug; 31(4):477-489. PubMed ID: 29344753
[TBL] [Abstract][Full Text] [Related]
4. Brain tumor segmentation with Vander Lugt correlator based active contour.
Essadike A; Ouabida E; Bouzid A
Comput Methods Programs Biomed; 2018 Jul; 160():103-117. PubMed ID: 29728237
[TBL] [Abstract][Full Text] [Related]
5. A mathematical theory of shape and neuro-fuzzy methodology-based diagnostic analysis: a comparative study on early detection and treatment planning of brain cancer.
Kar S; Majumder DD
Int J Clin Oncol; 2017 Aug; 22(4):667-681. PubMed ID: 28321787
[TBL] [Abstract][Full Text] [Related]
6. A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors.
Chen B; Zhang L; Chen H; Liang K; Chen X
Comput Methods Programs Biomed; 2021 Mar; 200():105797. PubMed ID: 33317871
[TBL] [Abstract][Full Text] [Related]
7. Brain tumor detection using statistical and machine learning method.
Amin J; Sharif M; Raza M; Saba T; Anjum MA
Comput Methods Programs Biomed; 2019 Aug; 177():69-79. PubMed ID: 31319962
[TBL] [Abstract][Full Text] [Related]
8. BirCat Optimization for Automatic Segmentation of Brain Tumors and Pixel Change Detection Using Post-operative MRI Images.
K V S; Sugitha N
J Digit Imaging; 2023 Apr; 36(2):647-665. PubMed ID: 36544068
[TBL] [Abstract][Full Text] [Related]
9. A level set method based on domain transformation and bias correction for MRI brain tumor segmentation.
Khosravanian A; Rahmanimanesh M; Keshavarzi P; Mozaffari S
J Neurosci Methods; 2021 Mar; 352():109091. PubMed ID: 33515604
[TBL] [Abstract][Full Text] [Related]
10. Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.
Cui S; Mao L; Jiang J; Liu C; Xiong S
J Healthc Eng; 2018; 2018():4940593. PubMed ID: 29755716
[TBL] [Abstract][Full Text] [Related]
11. Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI.
Soltaninejad M; Yang G; Lambrou T; Allinson N; Jones TL; Barrick TR; Howe FA; Ye X
Int J Comput Assist Radiol Surg; 2017 Feb; 12(2):183-203. PubMed ID: 27651330
[TBL] [Abstract][Full Text] [Related]
12. Automated brain tumor segmentation from multi-slices FLAIR MRI images.
Eltayeb EN; Salem NM; Al-Atabany W
Biomed Mater Eng; 2019; 30(4):449-462. PubMed ID: 31476145
[TBL] [Abstract][Full Text] [Related]
13. Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images.
Naceur MB; Saouli R; Akil M; Kachouri R
Comput Methods Programs Biomed; 2018 Nov; 166():39-49. PubMed ID: 30415717
[TBL] [Abstract][Full Text] [Related]
14. An optimal brain tumor segmentation algorithm for clinical MRI dataset with low resolution and non-contiguous slices.
Battalapalli D; Rao BVVSNP; Yogeeswari P; Kesavadas C; Rajagopalan V
BMC Med Imaging; 2022 May; 22(1):89. PubMed ID: 35568820
[TBL] [Abstract][Full Text] [Related]
15. 3D dense connectivity network with atrous convolutional feature pyramid for brain tumor segmentation in magnetic resonance imaging of human heads.
Zhou Z; He Z; Shi M; Du J; Chen D
Comput Biol Med; 2020 Jun; 121():103766. PubMed ID: 32568669
[TBL] [Abstract][Full Text] [Related]
16. Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine.
Perkuhn M; Stavrinou P; Thiele F; Shakirin G; Mohan M; Garmpis D; Kabbasch C; Borggrefe J
Invest Radiol; 2018 Nov; 53(11):647-654. PubMed ID: 29863600
[TBL] [Abstract][Full Text] [Related]
17. Automatic metastatic brain tumor segmentation for stereotactic radiosurgery applications.
Liu Y; Stojadinovic S; Hrycushko B; Wardak Z; Lu W; Yan Y; Jiang SB; Timmerman R; Abdulrahman R; Nedzi L; Gu X
Phys Med Biol; 2016 Dec; 61(24):8440-8461. PubMed ID: 27845915
[TBL] [Abstract][Full Text] [Related]
18. Brain MR Image Enhancement for Tumor Segmentation Using 3D U-Net.
Ullah F; Ansari SU; Hanif M; Ayari MA; Chowdhury MEH; Khandakar AA; Khan MS
Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833602
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates.
Pipitone J; Park MT; Winterburn J; Lett TA; Lerch JP; Pruessner JC; Lepage M; Voineskos AN; Chakravarty MM;
Neuroimage; 2014 Nov; 101():494-512. PubMed ID: 24784800
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]