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Computer-Aided Detection (CADe) and Segmentation Methods for Breast Cancer Using Magnetic Resonance Imaging (MRI).
J Magn Reson Imaging
January 2025
Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Breast cancer continues to be a major health concern, and early detection is vital for enhancing survival rates. Magnetic resonance imaging (MRI) is a key tool due to its substantial sensitivity for invasive breast cancers. Computer-aided detection (CADe) systems enhance the effectiveness of MRI by identifying potential lesions, aiding radiologists in focusing on areas of interest, extracting quantitative features, and integrating with computer-aided diagnosis (CADx) pipelines.
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Radiology
January 2025
From the Department of Radiology, Montpellier Cancer Institute, University of Montpellier, 208 av des Apothicaires, 34090 Montpellier, France (S.N.); PINKCC Laboratory, Montpellier Cancer Research Institute, University of Montpellier, Montpellier, France (S.N.); Jones Radiology, South Australia, Australia (K.G.); The University of Adelaide, South Australia, Australia (K.G.); Department of Radiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands (D.M.J.L.); GROW School for Oncology and Reproduction, University of Maastricht, Maastricht, the Netherlands (D.M.J.L.); Department of Radiology, McGill University, Montreal, Quebec, Canada (C.R.); Department of Radiology, Guy's and St Thomas NHS Foundation Trust, London, United Kingdom (V.G.); School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, London, United Kingdom (V.G.); Department of Radiology, Oregon Health & Science University, Portland, Ore (E.K.); Bordeaux Colorectal Institute, Bordeaux, France (Q.D.); Department of Radiology, Royal Marsden, London, United Kingdom (G.B.); Department of Radiology, Imperial College London, London, United Kingdom (G.B.).
Over the past decade, advancements in rectal cancer research have reshaped treatment paradigms. Historically, treatment for locally advanced rectal cancer has focused on neoadjuvant long-course chemoradiotherapy, followed by total mesorectal excision. Interest in organ preservation strategies has been strengthened by the introduction of total neoadjuvant therapy with improved rates of complete clinical response.
View Article and Find Full Text PDFMachine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models from the RSNA 2022 Cervical Spine Fracture AI Challenge.
AJR Am J Roentgenol
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Department of Medical Imaging, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on re-evaluation; such studies do not capture the full extent of missed fractures. To use machine-learning (ML) models to identify cervical spine fractures on CT missed by interpreting radiologists, characterize the nature of these fractures, and assess their clinical significance. This retrospective study included all cervical spine CT examinations performed in adult patients in the emergency department between January 1, 2018 and December 31, 2022.
View Article and Find Full Text PDFCANAIRI: the Collaboration for Translational Artificial Intelligence Trials in healthcare.
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Musculoskeletal Computed Tomography: How to Add Value When Reporting Adult Lower Limb Trauma.
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November 2024
Department of Trauma and Orthopaedics, University Hospitals of Morecambe Bay NHS Trust, Lancaster, United Kingdom.
Computed tomography plays an ever-increasing role in the management of fractures and dislocations due to its capability in efficiently providing multiplanar reformats and 3-dimensional volume rendered images. It can reveal findings that are occult on plain radiography and therefore allow for more accurate decision making with regard to fracture classification and management. Clinical radiologists play a critical role in facilitating the processing of imaging to provide adequate image reformats in the desired planes, producing 3 dimensional images but most crucially identifying pertinent findings, which will contribute between the selection of nonoperative and operative management and potentially influence surgical technique.
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