209 related articles for article (PubMed ID: 36396792)
21. 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]
22. Catheter segmentation in X-ray fluoroscopy using synthetic data and transfer learning with light U-nets.
Gherardini M; Mazomenos E; Menciassi A; Stoyanov D
Comput Methods Programs Biomed; 2020 Aug; 192():105420. PubMed ID: 32171151
[TBL] [Abstract][Full Text] [Related]
23. Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.
Ye LY; Miao XY; Cai WS; Xu WJ
Comput Methods Programs Biomed; 2022 Jun; 221():106770. PubMed ID: 35640389
[TBL] [Abstract][Full Text] [Related]
24. Deep learning kidney segmentation with very limited training data using a cascaded convolution neural network.
Guo J; Odu A; Pedrosa I
PLoS One; 2022; 17(5):e0267753. PubMed ID: 35533181
[TBL] [Abstract][Full Text] [Related]
25. DFR-U-Net: Dual residual and feature fusion network for ulna and radius segmentation on dual-energy X-ray absorptiometry images.
Yang F; Weng X; Wu Y; Miao Y; Lei P; Hu Z
J Xray Sci Technol; 2023; 31(3):641-653. PubMed ID: 37038803
[TBL] [Abstract][Full Text] [Related]
26. Deep neural network for automated simultaneous intervertebral disc (IVDs) identification and segmentation of multi-modal MR images.
Das P; Pal C; Acharyya A; Chakrabarti A; Basu S
Comput Methods Programs Biomed; 2021 Jun; 205():106074. PubMed ID: 33906011
[TBL] [Abstract][Full Text] [Related]
27. Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images.
Choi H; Jeon KJ; Kim YH; Ha EG; Lee C; Han SS
Sci Rep; 2022 Aug; 12(1):14009. PubMed ID: 35978086
[TBL] [Abstract][Full Text] [Related]
28. Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging.
Gross M; Spektor M; Jaffe A; Kucukkaya AS; Iseke S; Haider SP; Strazzabosco M; Chapiro J; Onofrey JA
PLoS One; 2021; 16(12):e0260630. PubMed ID: 34852007
[TBL] [Abstract][Full Text] [Related]
29. Comparison of automated segmentation techniques for magnetic resonance images of the prostate.
Isaksson LJ; Pepa M; Summers P; Zaffaroni M; Vincini MG; Corrao G; Mazzola GC; Rotondi M; Lo Presti G; Raimondi S; Gandini S; Volpe S; Haron Z; Alessi S; Pricolo P; Mistretta FA; Luzzago S; Cattani F; Musi G; Cobelli O; Cremonesi M; Orecchia R; Marvaso G; Petralia G; Jereczek-Fossa BA
BMC Med Imaging; 2023 Feb; 23(1):32. PubMed ID: 36774463
[TBL] [Abstract][Full Text] [Related]
30. RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images.
Li YZ; Wang Y; Huang YH; Xiang P; Liu WX; Lai QQ; Gao YY; Xu MS; Guo YF
Comput Methods Programs Biomed; 2023 Apr; 231():107437. PubMed ID: 36863157
[TBL] [Abstract][Full Text] [Related]
31. Deep learning-based convolutional neural network for intramodality brain MRI synthesis.
Osman AFI; Tamam NM
J Appl Clin Med Phys; 2022 Apr; 23(4):e13530. PubMed ID: 35044073
[TBL] [Abstract][Full Text] [Related]
32. Knowledge-based and deep learning-based automated chest wall segmentation in magnetic resonance images of extremely dense breasts.
Verburg E; Wolterink JM; de Waard SN; Išgum I; van Gils CH; Veldhuis WB; Gilhuijs KGA
Med Phys; 2019 Oct; 46(10):4405-4416. PubMed ID: 31274194
[TBL] [Abstract][Full Text] [Related]
33. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.
Tong N; Gou S; Yang S; Cao M; Sheng K
Med Phys; 2019 Jun; 46(6):2669-2682. PubMed ID: 31002188
[TBL] [Abstract][Full Text] [Related]
34. Automated segmentation of head CT scans for computer-assisted craniomaxillofacial surgery applying a hierarchical patch-based stack of convolutional neural networks.
Steybe D; Poxleitner P; Metzger MC; Brandenburg LS; Schmelzeisen R; Bamberg F; Tran PH; Kellner E; Reisert M; Russe MF
Int J Comput Assist Radiol Surg; 2022 Nov; 17(11):2093-2101. PubMed ID: 35665881
[TBL] [Abstract][Full Text] [Related]
35. Evaluation of Spatial Attentive Deep Learning for Automatic Placental Segmentation on Longitudinal MRI.
Liu Y; Zabihollahy F; Yan R; Lee B; Janzen C; Devaskar SU; Sung K
J Magn Reson Imaging; 2023 May; 57(5):1533-1540. PubMed ID: 37021577
[TBL] [Abstract][Full Text] [Related]
36. Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net.
Zhang Y; Chen JH; Chang KT; Park VY; Kim MJ; Chan S; Chang P; Chow D; Luk A; Kwong T; Su MY
Acad Radiol; 2019 Nov; 26(11):1526-1535. PubMed ID: 30713130
[TBL] [Abstract][Full Text] [Related]
37. Automatic quadriceps and patellae segmentation of MRI with cascaded U
Cheng R; Crouzier M; Hug F; Tucker K; Juneau P; McCreedy E; Gandler W; McAuliffe MJ; Sheehan FT
Med Phys; 2022 Jan; 49(1):443-460. PubMed ID: 34755359
[TBL] [Abstract][Full Text] [Related]
38. Automated fibroglandular tissue segmentation in breast MRI using generative adversarial networks.
Ma X; Wang J; Zheng X; Liu Z; Long W; Zhang Y; Wei J; Lu Y
Phys Med Biol; 2020 May; 65(10):105006. PubMed ID: 32155611
[TBL] [Abstract][Full Text] [Related]
39. Multi-Scale deep learning framework for cochlea localization, segmentation and analysis on clinical ultra-high-resolution CT images.
Heutink F; Koch V; Verbist B; van der Woude WJ; Mylanus E; Huinck W; Sechopoulos I; Caballo M
Comput Methods Programs Biomed; 2020 Jul; 191():105387. PubMed ID: 32109685
[TBL] [Abstract][Full Text] [Related]
40. Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation.
Dieckhaus H; Meijboom R; Okar S; Wu T; Parvathaneni P; Mina Y; Chandran S; Waldman AD; Reich DS; Nair G
Top Magn Reson Imaging; 2022 Jun; 31(3):31-39. PubMed ID: 35767314
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
