146 related articles for article (PubMed ID: 34327627)
1. Multi-level Kronecker Convolutional Neural Network (ML-KCNN) for Glioma Segmentation from Multi-modal MRI Volumetric Data.
Ali MJ; Raza B; Shahid AR
J Digit Imaging; 2021 Aug; 34(4):905-921. PubMed ID: 34327627
[TBL] [Abstract][Full Text] [Related]
2. [Fully Automatic Glioma Segmentation Algorithm of Magnetic Resonance Imaging Based on 3D-UNet With More Global Contextual Feature Extraction: An Improvement on Insufficient Extraction of Global Features].
Tian H; Wang Y; Ji Y; Rahman MM
Sichuan Da Xue Xue Bao Yi Xue Ban; 2024 Mar; 55(2):447-454. PubMed ID: 38645864
[TBL] [Abstract][Full Text] [Related]
3. Deeply supervised 3D fully convolutional networks with group dilated convolution for automatic MRI prostate segmentation.
Wang B; Lei Y; Tian S; Wang T; Liu Y; Patel P; Jani AB; Mao H; Curran WJ; Liu T; Yang X
Med Phys; 2019 Apr; 46(4):1707-1718. PubMed ID: 30702759
[TBL] [Abstract][Full Text] [Related]
4. Attention-guided multi-scale context aggregation network for multi-modal brain glioma segmentation.
Wu S; Cao Y; Li X; Liu Q; Ye Y; Liu X; Zeng L; Tian M
Med Phys; 2023 Dec; 50(12):7629-7640. PubMed ID: 37151131
[TBL] [Abstract][Full Text] [Related]
5. Fully connected network with multi-scale dilation convolution module in evaluating atrial septal defect based on MRI segmentation.
Chen H; Yan S; Xie M; Ye Y; Ye Y; Zhu D; Su L; Huang J
Comput Methods Programs Biomed; 2022 Mar; 215():106608. PubMed ID: 35063713
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. A multiple-channel and atrous convolution network for ultrasound image segmentation.
Zhang L; Zhang J; Li Z; Song Y
Med Phys; 2020 Dec; 47(12):6270-6285. PubMed ID: 33007105
[TBL] [Abstract][Full Text] [Related]
8. Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.
Lavdas I; Glocker B; Kamnitsas K; Rueckert D; Mair H; Sandhu A; Taylor SA; Aboagye EO; Rockall AG
Med Phys; 2017 Oct; 44(10):5210-5220. PubMed ID: 28756622
[TBL] [Abstract][Full Text] [Related]
9. Brain tumor segmentation using holistically nested neural networks in MRI images.
Zhuge Y; Krauze AV; Ning H; Cheng JY; Arora BC; Camphausen K; Miller RW
Med Phys; 2017 Oct; 44(10):5234-5243. PubMed ID: 28736864
[TBL] [Abstract][Full Text] [Related]
10. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
[TBL] [Abstract][Full Text] [Related]
11. DeepSeg: deep neural network framework for automatic brain tumor segmentation using magnetic resonance FLAIR images.
Zeineldin RA; Karar ME; Coburger J; Wirtz CR; Burgert O
Int J Comput Assist Radiol Surg; 2020 Jun; 15(6):909-920. PubMed ID: 32372386
[TBL] [Abstract][Full Text] [Related]
12. Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology.
Rachmadi MF; Valdés-Hernández MDC; Agan MLF; Di Perri C; Komura T;
Comput Med Imaging Graph; 2018 Jun; 66():28-43. PubMed ID: 29523002
[TBL] [Abstract][Full Text] [Related]
13. DFP-ResUNet:Convolutional Neural Network with a Dilated Convolutional Feature Pyramid for Multimodal Brain Tumor Segmentation.
Wang J; Gao J; Ren J; Luan Z; Yu Z; Zhao Y; Zhao Y
Comput Methods Programs Biomed; 2021 Sep; 208():106208. PubMed ID: 34174763
[TBL] [Abstract][Full Text] [Related]
14. SDResU-Net: Separable and Dilated Residual U-Net for MRI Brain Tumor Segmentation.
Zhang J; Lv X; Sun Q; Zhang Q; Wei X; Liu B
Curr Med Imaging; 2020; 16(6):720-728. PubMed ID: 32723244
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Automatic Segmentation of MRI of Brain Tumor Using Deep Convolutional Network.
Zhou R; Hu S; Ma B; Ma B
Biomed Res Int; 2022; 2022():4247631. PubMed ID: 35757482
[TBL] [Abstract][Full Text] [Related]
17. Automated glioma grading on conventional MRI images using deep convolutional neural networks.
Zhuge Y; Ning H; Mathen P; Cheng JY; Krauze AV; Camphausen K; Miller RW
Med Phys; 2020 Jul; 47(7):3044-3053. PubMed ID: 32277478
[TBL] [Abstract][Full Text] [Related]
18. Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF.
Li Z; Wang Y; Yu J; Shi Z; Guo Y; Chen L; Mao Y
J Healthc Eng; 2017; 2017():9283480. PubMed ID: 29065666
[TBL] [Abstract][Full Text] [Related]
19. Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.
Hu Y; Guo Y; Wang Y; Yu J; Li J; Zhou S; Chang C
Med Phys; 2019 Jan; 46(1):215-228. PubMed ID: 30374980
[TBL] [Abstract][Full Text] [Related]
20. Automated Segmentation of Colorectal Tumor in 3D MRI Using 3D Multiscale Densely Connected Convolutional Neural Network.
Soomro MH; Coppotelli M; Conforto S; Schmid M; Giunta G; Del Secco L; Neri E; Caruso D; Rengo M; Laghi A
J Healthc Eng; 2019; 2019():1075434. PubMed ID: 30838121
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
