190 related articles for article (PubMed ID: 38067324)
1. RFS+: A Clinically Adaptable and Computationally Efficient Strategy for Enhanced Brain Tumor Segmentation.
Duman A; Karakuş O; Sun X; Thomas S; Powell J; Spezi E
Cancers (Basel); 2023 Nov; 15(23):. PubMed ID: 38067324
[TBL] [Abstract][Full Text] [Related]
2. Reducing annotation burden in MR: A novel MR-contrast guided contrastive learning approach for image segmentation.
Umapathy L; Brown T; Mushtaq R; Greenhill M; Lu J; Martin D; Altbach M; Bilgin A
Med Phys; 2024 Apr; 51(4):2707-2720. PubMed ID: 37956263
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Asymmetric Ensemble of Asymmetric U-Net Models for Brain Tumor Segmentation With Uncertainty Estimation.
Rosas-Gonzalez S; Birgui-Sekou T; Hidane M; Zemmoura I; Tauber C
Front Neurol; 2021; 12():609646. PubMed ID: 34659077
[TBL] [Abstract][Full Text] [Related]
5. Bridged-U-Net-ASPP-EVO and Deep Learning Optimization for Brain Tumor Segmentation.
Yousef R; Khan S; Gupta G; Albahlal BM; Alajlan SA; Ali A
Diagnostics (Basel); 2023 Aug; 13(16):. PubMed ID: 37627893
[TBL] [Abstract][Full Text] [Related]
6. Identifying core MRI sequences for reliable automatic brain metastasis segmentation.
Buchner JA; Peeken JC; Etzel L; Ezhov I; Mayinger M; Christ SM; Brunner TB; Wittig A; Menze BH; Zimmer C; Meyer B; Guckenberger M; Andratschke N; El Shafie RA; Debus J; Rogers S; Riesterer O; Schulze K; Feldmann HJ; Blanck O; Zamboglou C; Ferentinos K; Bilger A; Grosu AL; Wolff R; Kirschke JS; Eitz KA; Combs SE; Bernhardt D; Rueckert D; Piraud M; Wiestler B; Kofler F
Radiother Oncol; 2023 Nov; 188():109901. PubMed ID: 37678623
[TBL] [Abstract][Full Text] [Related]
7. A Novel Approach for Fully Automatic Intra-Tumor Segmentation With 3D U-Net Architecture for Gliomas.
Baid U; Talbar S; Rane S; Gupta S; Thakur MH; Moiyadi A; Sable N; Akolkar M; Mahajan A
Front Comput Neurosci; 2020; 14():10. PubMed ID: 32132913
[No Abstract] [Full Text] [Related]
8. A Memory-efficient Deep Framework for Multi-Modal MRI-based Brain Tumor Segmentation.
Hashemi N; Masoudnia S; Nejad A; Nazem-Zadeh MR
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3749-3752. PubMed ID: 36086352
[TBL] [Abstract][Full Text] [Related]
9. Application of deep learning for automatic segmentation of brain tumors on magnetic resonance imaging: a heuristic approach in the clinical scenario.
Di Ieva A; Russo C; Liu S; Jian A; Bai MY; Qian Y; Magnussen JS
Neuroradiology; 2021 Aug; 63(8):1253-1262. PubMed ID: 33501512
[TBL] [Abstract][Full Text] [Related]
10. Clinical capability of modern brain tumor segmentation models.
Berkley A; Saueressig C; Shukla U; Chowdhury I; Munoz-Gauna A; Shehu O; Singh R; Munbodh R
Med Phys; 2023 Aug; 50(8):4943-4959. PubMed ID: 36847185
[TBL] [Abstract][Full Text] [Related]
11. MSFR-Net: Multi-modality and single-modality feature recalibration network for brain tumor segmentation.
Li X; Jiang Y; Li M; Zhang J; Yin S; Luo H
Med Phys; 2023 Apr; 50(4):2249-2262. PubMed ID: 35962724
[TBL] [Abstract][Full Text] [Related]
12. An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.
Fashandi H; Kuling G; Lu Y; Wu H; Martel AL
Med Phys; 2019 Mar; 46(3):1230-1244. PubMed ID: 30609062
[TBL] [Abstract][Full Text] [Related]
13. A radiomics-incorporated deep ensemble learning model for multi-parametric MRI-based glioma segmentation.
Chen Y; Yang Z; Zhao J; Adamson J; Sheng Y; Yin FF; Wang C
Phys Med Biol; 2023 Sep; 68(18):. PubMed ID: 37586382
[No Abstract] [Full Text] [Related]
14. Magnetic resonance image-based brain tumour segmentation methods: A systematic review.
Bhalodiya JM; Lim Choi Keung SN; Arvanitis TN
Digit Health; 2022; 8():20552076221074122. PubMed ID: 35340900
[TBL] [Abstract][Full Text] [Related]
15. Scalable Swin Transformer network for brain tumor segmentation from incomplete MRI modalities.
Zhang D; Wang C; Chen T; Chen W; Shen Y
Artif Intell Med; 2024 Mar; 149():102788. PubMed ID: 38462288
[TBL] [Abstract][Full Text] [Related]
16. Cascaded mutual enhancing networks for brain tumor subregion segmentation in multiparametric MRI.
Momin S; Lei Y; Tian Z; Roper J; Lin J; Kahn S; Shu HK; Bradley J; Liu T; Yang X
Phys Med Biol; 2022 Apr; 67(8):. PubMed ID: 35299156
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.
Laukamp KR; Pennig L; Thiele F; Reimer R; Görtz L; Shakirin G; Zopfs D; Timmer M; Perkuhn M; Borggrefe J
Clin Neuroradiol; 2021 Jun; 31(2):357-366. PubMed ID: 32060575
[TBL] [Abstract][Full Text] [Related]
19. Robust Ensemble of Two Different Multimodal Approaches to Segment 3D Ischemic Stroke Segmentation Using Brain Tumor Representation Among Multiple Center Datasets.
Jeong H; Lim H; Yoon C; Won J; Lee GY; de la Rosa E; Kirschke JS; Kim B; Kim N; Kim C
J Imaging Inform Med; 2024 May; ():. PubMed ID: 38693333
[TBL] [Abstract][Full Text] [Related]
20. A single stage knowledge distillation network for brain tumor segmentation on limited MR image modalities.
Choi Y; Al-Masni MA; Jung KJ; Yoo RE; Lee SY; Kim DH
Comput Methods Programs Biomed; 2023 Oct; 240():107644. PubMed ID: 37307766
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
