130 related articles for article (PubMed ID: 34422120)
41. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH
Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353
[TBL] [Abstract][Full Text] [Related]
42. Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Tajbakhsh N; Shin JY; Gurudu SR; Hurst RT; Kendall CB; Gotway MB; Jianming Liang
IEEE Trans Med Imaging; 2016 May; 35(5):1299-1312. PubMed ID: 26978662
[TBL] [Abstract][Full Text] [Related]
43. Automatic Diagnosis of Stage of COVID-19 Patients using an Ensemble of Transfer Learning with Convolutional Neural Networks Based on Computed Tomography Images.
Gifani P; Vafaeezadeh M; Ghorbani M; Mehri-Kakavand G; Pursamimi M; Shalbaf A; Davanloo AA
J Med Signals Sens; 2023; 13(2):101-109. PubMed ID: 37448543
[TBL] [Abstract][Full Text] [Related]
44. A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.
Mylonas A; Keall PJ; Booth JT; Shieh CC; Eade T; Poulsen PR; Nguyen DT
Med Phys; 2019 May; 46(5):2286-2297. PubMed ID: 30929254
[TBL] [Abstract][Full Text] [Related]
45. Corona-Nidaan: lightweight deep convolutional neural network for chest X-Ray based COVID-19 infection detection.
Chakraborty M; Dhavale SV; Ingole J
Appl Intell (Dordr); 2021; 51(5):3026-3043. PubMed ID: 34764582
[TBL] [Abstract][Full Text] [Related]
46. COFE-Net: An ensemble strategy for Computer-Aided Detection for COVID-19.
Banerjee A; Bhattacharya R; Bhateja V; Singh PK; Lay-Ekuakille A; Sarkar R
Measurement (Lond); 2022 Jan; 187():110289. PubMed ID: 34663998
[TBL] [Abstract][Full Text] [Related]
47. Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison.
de Vente C; Boulogne LH; Venkadesh KV; Sital C; Lessmann N; Jacobs C; Sanchez CI; van Ginneken B
IEEE Trans Artif Intell; 2022 Apr; 3(2):129-138. PubMed ID: 35582210
[TBL] [Abstract][Full Text] [Related]
48. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.
Huang W; Xue Y; Wu Y
PLoS One; 2019; 14(7):e0219369. PubMed ID: 31299053
[TBL] [Abstract][Full Text] [Related]
49. Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans.
Farhangi MM; Petrick N; Sahiner B; Frigui H; Amini AA; Pezeshk A
Med Phys; 2020 Jun; 47(5):2150-2160. PubMed ID: 32030769
[TBL] [Abstract][Full Text] [Related]
50. 3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT.
Pezeshk A; Hamidian S; Petrick N; Sahiner B
IEEE J Biomed Health Inform; 2019 Sep; 23(5):2080-2090. PubMed ID: 30418929
[TBL] [Abstract][Full Text] [Related]
51. Improving effectiveness of different deep learning-based models for detecting COVID-19 from computed tomography (CT) images.
Acar E; Şahin E; Yılmaz İ
Neural Comput Appl; 2021; 33(24):17589-17609. PubMed ID: 34345118
[TBL] [Abstract][Full Text] [Related]
52. A bilinear convolutional neural network for lung nodules classification on CT images.
Mastouri R; Khlifa N; Neji H; Hantous-Zannad S
Int J Comput Assist Radiol Surg; 2021 Jan; 16(1):91-101. PubMed ID: 33140257
[TBL] [Abstract][Full Text] [Related]
53. COVID-19 identification from volumetric chest CT scans using a progressively resized 3D-CNN incorporating segmentation, augmentation, and class-rebalancing.
Hasan MK; Jawad MT; Hasan KNI; Partha SB; Masba MMA; Saha S; Moni MA
Inform Med Unlocked; 2021; 26():100709. PubMed ID: 34642640
[TBL] [Abstract][Full Text] [Related]
54. Diagnosis of Pediatric Pneumonia with Ensemble of Deep Convolutional Neural Networks in Chest X-Ray Images.
Ayan E; Karabulut B; Ünver HM
Arab J Sci Eng; 2022; 47(2):2123-2139. PubMed ID: 34540526
[TBL] [Abstract][Full Text] [Related]
55. Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques.
Apostolopoulos ID; Pintelas EG; Livieris IE; Apostolopoulos DJ; Papathanasiou ND; Pintelas PE; Panayiotakis GS
Med Biol Eng Comput; 2021 Jun; 59(6):1299-1310. PubMed ID: 34003394
[TBL] [Abstract][Full Text] [Related]
56. Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies.
Vivanti R; Joskowicz L; Lev-Cohain N; Ephrat A; Sosna J
Med Biol Eng Comput; 2018 Sep; 56(9):1699-1713. PubMed ID: 29524116
[TBL] [Abstract][Full Text] [Related]
57. Leveraging deep learning for COVID-19 diagnosis through chest imaging.
Khurana Y; Soni U
Neural Comput Appl; 2022; 34(16):14003-14012. PubMed ID: 35462631
[TBL] [Abstract][Full Text] [Related]
58. The investigation of multiresolution approaches for chest X-ray image based COVID-19 detection.
Ismael AM; Şengür A
Health Inf Sci Syst; 2020 Dec; 8(1):29. PubMed ID: 33014355
[TBL] [Abstract][Full Text] [Related]
59. A novel comparative study for detection of Covid-19 on CT lung images using texture analysis, machine learning, and deep learning methods.
Yasar H; Ceylan M
Multimed Tools Appl; 2021; 80(4):5423-5447. PubMed ID: 33041635
[TBL] [Abstract][Full Text] [Related]
60. Computer aid screening of COVID-19 using X-ray and CT scan images: An inner comparison.
Sethy PK; Behera SK; Anitha K; Pandey C; Khan MR
J Xray Sci Technol; 2021; 29(2):197-210. PubMed ID: 33492267
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]