Computer-aided diagnosis in medical imaging: Historical review, current status and future potential

By Kunio Doi. Comput. Medical Imaging Graph., 2007

1,855 citations recorded by the source corpus.

Subfields: Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/66783753253af1ed5bc2b3410035b7c6b27f925d

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In Pulmonary and Respiratory Medicine

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

A deep learning framework for supporting the classification of breast lesions in ultrasound images (2017, methodology): “…is a computerized procedure to provide a second objective opinion on the interpretation of a medical image and diagnosis (Chen et al 2003, Joo et al 2004, Awai et al 2006, McCarville et al 2006, Doi 2007, Giger et al 2008, Drukker et al 2009, Cheng et al 2010, van Ginneken 2011, Giger et al 2013).”
3D Deep Learning on Medical Images: A Review (2020, background): “Common radiological investigation modalities include X-ray, Computed Tomography (CT), Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), functional MRI (fMRI), and Magnetic Resonance Imaging (MRI), [1]–[4].”
Radiomics: Images Are More than Pictures, They Are Data (2015, neutral): “Early successes of CAD have been greatest in breast cancer imaging (2,3).”
Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning (2017, methodology): “Computer-aided diagnosis (CAD), with the two-step approach advocated by Lodwick, became more popular in the 1980s and beyond, and it was widely applied to chest imaging in the seminal work of the group of Kunio Doi at the University of Chicago [4].”
Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration (2018, background): “18 Starting with detection of breast cancer on mammograms, 19 CAD has been extended to several other diseases such as lung cancer, 20 colon cancer 21 and more recently several brain disorders such as Alzheimer ’ s disease.”
Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data (2013, methodology): “is used widely for diagnosis [1], treatment planning [2], and assessing response to treatment [3].”
Endowing a Content-Based Medical Image Retrieval System with Perceptual Similarity Using Ensemble Strategy (2016, background): “[1], an alternative CADx process would provide a set of similar past cases and the likelihood of malignancy (%).”
Deep learning based brain tumor segmentation: a survey (2020, neutral): “computer-aided diagnosis [1], medical record data management [2], medical robots [3] and medical image analysis [4].”
Medical image analysis with artificial neural networks (2010, background): “Some relevant survey papers can be found in [59, 60, 61].”
Computer-aided classification of lung nodules on computed tomography images via deep learning technique (2015, neutral): “Computer-aided diagnosis (CAD) is a research field concerned with offering a quantitative opinion to improve the clinical diagnostic process.(4,5) One of the major purposes of CAD is to automatically differentiate the malignant/benign nature of tumors/lesions based on numeric image features to assis”