Original Research
Published on 15 Feb 2024
Beyond images: an integrative multi-modal approach to chest x-ray report generation
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2024.1339612
- 1,575 views
- 1 citation
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71 articles
Articles
Original Research
Published on 18 Jan 2024
Using a generative adversarial network to generate synthetic MRI images for multi-class automatic segmentation of brain tumors
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1336902
- 2,225 views
- 3 citations
Editorial
Published on 10 Jan 2024
Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1349830
- 1,370 views
- 1 citation
Brief Research Report
Published on 08 Jan 2024
RoMIA: a framework for creating Robust Medical Imaging AI models for chest radiographs
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1274273
- 1,107 views
- 1 citation
Review
Published on 05 Jan 2024
Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1326831
- 3,395 views
- 4 citations
Editorial
Published on 18 Dec 2023
Editorial: Radiomics and radiogenomics in genitourinary oncology: artificial intelligence and deep learning applications
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1325594
- 1,212 views
- 1 citation
Original Research
Published on 21 Nov 2023
Radiomic analysis of the proximal femur in osteoporosis women using 3T MRI
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1293865
- 1,412 views
- 2 citations
Retraction
Published on 09 Nov 2023
Retraction: CT-based risk factors for mortality of patients with COVID-19 pneumonia in Wuhan, China: a retrospective study
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1330251
- 849 views
Original Research
Published on 11 Oct 2023
Retrospective T2 quantification from conventional weighted MRI of the prostate based on deep learning
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1223377
- 1,453 views
- 1 citation
Original Research
Published on 21 Sep 2023
Selecting the best optimizers for deep learning–based medical image segmentation
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1175473
- 4,362 views
- 4 citations
Original Research
Published on 15 Sep 2023
AI in the Loop: functionalizing fold performance disagreement to monitor automated medical image segmentation workflows
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1223294
- 858 views
- 1 citation
Original Research
Published on 11 Sep 2023
High angular diffusion tensor imaging estimation from minimal evenly distributed diffusion gradient directions
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1238566
- 1,395 views
- 1 citation
Original Research
Published on 07 Sep 2023
Evaluating automated longitudinal tumor measurements for glioblastoma response assessment
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1211859
- 1,988 views
Original Research
Published on 05 Sep 2023
From coarse to fine: a deep 3D probability volume contours framework for tumour segmentation and dose painting in PET images
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1225215
- 1,130 views
Original Research
Published on 04 Sep 2023
Retrospective quantification of clinical abdominal DCE-MRI using pharmacokinetics-informed deep learning: a proof-of-concept study
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1168901
- 1,816 views
- 2 citations
Mini Review
Published on 24 Aug 2023
Spatial assessments in texture analysis: what the radiologist needs to know
in Artificial Intelligence in Radiology
Frontiers in Radiology
doi 10.3389/fradi.2023.1240544
- 1,804 views
- 2 citations