233 related articles for article (PubMed ID: 32008563)
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. Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.
Pereira S; Meier R; McKinley R; Wiest R; Alves V; Silva CA; Reyes M
Med Image Anal; 2018 Feb; 44():228-244. PubMed ID: 29289703
[TBL] [Abstract][Full Text] [Related]
23. Brain tumor detection with integrating traditional and computational intelligence approaches across diverse imaging modalities - Challenges and future directions.
Batool A; Byun YC
Comput Biol Med; 2024 Jun; 175():108412. PubMed ID: 38691914
[TBL] [Abstract][Full Text] [Related]
24. Automated assessment of thigh composition using machine learning for Dixon magnetic resonance images.
Yang YX; Chong MS; Tay L; Yew S; Yeo A; Tan CH
MAGMA; 2016 Oct; 29(5):723-31. PubMed ID: 27026244
[TBL] [Abstract][Full Text] [Related]
25. A new approach for brain tumor diagnosis system: Single image super resolution based maximum fuzzy entropy segmentation and convolutional neural network.
Sert E; Özyurt F; Doğantekin A
Med Hypotheses; 2019 Dec; 133():109413. PubMed ID: 31586812
[TBL] [Abstract][Full Text] [Related]
26. Automatic glioma segmentation based on adaptive superpixel.
Wu Y; Zhao Z; Wu W; Lin Y; Wang M
BMC Med Imaging; 2019 Aug; 19(1):73. PubMed ID: 31443642
[TBL] [Abstract][Full Text] [Related]
27. A review on brain tumor segmentation of MRI images.
Wadhwa A; Bhardwaj A; Singh Verma V
Magn Reson Imaging; 2019 Sep; 61():247-259. PubMed ID: 31200024
[TBL] [Abstract][Full Text] [Related]
28. MRI Gibbs-ringing artifact reduction by means of machine learning using convolutional neural networks.
Zhang Q; Ruan G; Yang W; Liu Y; Zhao K; Feng Q; Chen W; Wu EX; Feng Y
Magn Reson Med; 2019 Dec; 82(6):2133-2145. PubMed ID: 31373061
[TBL] [Abstract][Full Text] [Related]
29. 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]
30. Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review.
Soomro TA; Zheng L; Afifi AJ; Ali A; Soomro S; Yin M; Gao J
IEEE Rev Biomed Eng; 2023; 16():70-90. PubMed ID: 35737636
[TBL] [Abstract][Full Text] [Related]
31. 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]
32. A potential field segmentation based method for tumor segmentation on multi-parametric MRI of glioma cancer patients.
Sun R; Wang K; Guo L; Yang C; Chen J; Ti Y; Sa Y
BMC Med Imaging; 2019 Jun; 19(1):48. PubMed ID: 31208349
[TBL] [Abstract][Full Text] [Related]
33. MRI Brain Tumour Segmentation Using Hybrid Clustering and Classification by Back Propagation Algorithm.
M M; P S
Asian Pac J Cancer Prev; 2018 Nov; 19(11):3257-3263. PubMed ID: 30486629
[TBL] [Abstract][Full Text] [Related]
34. Using deep learning to segment breast and fibroglandular tissue in MRI volumes.
Dalmış MU; Litjens G; Holland K; Setio A; Mann R; Karssemeijer N; Gubern-Mérida A
Med Phys; 2017 Feb; 44(2):533-546. PubMed ID: 28035663
[TBL] [Abstract][Full Text] [Related]
35. Glioma Tumor Grade Identification Using Artificial Intelligent Techniques.
Ahammed Muneer K V ; Rajendran VR; K PJ
J Med Syst; 2019 Mar; 43(5):113. PubMed ID: 30900029
[TBL] [Abstract][Full Text] [Related]
36. Fusion based Glioma brain tumor detection and segmentation using ANFIS classification.
Selvapandian A; Manivannan K
Comput Methods Programs Biomed; 2018 Nov; 166():33-38. PubMed ID: 30415716
[TBL] [Abstract][Full Text] [Related]
37. Evolution of Deep Learning Algorithms for MRI-Based Brain Tumor Image Segmentation.
Shal K; Choudhry MS
Crit Rev Biomed Eng; 2021; 49(1):77-94. PubMed ID: 34347989
[TBL] [Abstract][Full Text] [Related]
38. Hybrid machine learning-based breast cancer segmentation framework using ultrasound images with optimal weighted features.
Vijayan S; Panneerselvam R; Roshini TV
Cell Biochem Funct; 2024 Jun; 42(4):e4054. PubMed ID: 38783623
[TBL] [Abstract][Full Text] [Related]
39. Round Randomized Learning Vector Quantization for Brain Tumor Imaging.
Sheikh Abdullah SN; Bohani FA; Nayef BH; Sahran S; Al Akash O; Iqbal Hussain R; Ismail F
Comput Math Methods Med; 2016; 2016():8603609. PubMed ID: 27516807
[TBL] [Abstract][Full Text] [Related]
40. 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]
[Previous] [Next] [New Search]