Fully automated volumetric measurement of malignant pleural mesothelioma by deep learning AI: validation and comparison with modified RECIST response criteria.

Kidd, Andrew C; Anderson, Owen; Cowell, Gordon W; Weir, Alexander J; Voisey, Jeremy P; Evison, Matthew; Tsim, Selina; Goatman, Keith A; Blyth, Kevin G

Kidd, Andrew C; Anderson, Owen; Cowell, Gordon W; Weir, Alexander J; Voisey, Jeremy P; Evison, Matthew; Tsim, Selina; Goatman, Keith A; Blyth, Kevin G.

Affiliation

Kidd AC; Glasgow Pleural Disease Unit, Queen Elizabeth University Hospital, Glasgow, UK.
Anderson O; School of Computing Science, University of Glasgow, Glasgow, UK.
Cowell GW; Canon Medical Research Europe Ltd, Edinburgh, UK.
Weir AJ; Department of Imaging, Queen Elizabeth University Hospital, Glasgow, UK.
Voisey JP; Canon Medical Research Europe Ltd, Edinburgh, UK.
Evison M; Canon Medical Research Europe Ltd, Edinburgh, UK.
Tsim S; Department of Respiratory Medicine, University Hospital of South Manchester, Manchester, UK.
Goatman KA; Glasgow Pleural Disease Unit, Queen Elizabeth University Hospital, Glasgow, UK.
Blyth KG; Institute of Cancer Sciences, University of Glasgow, Glasgow, UK.

Thorax ; 77(12): 1251-1259, 2022 12.

Article in En | MEDLINE | ID: mdl-35110367

Subject(s)
Key words

imaging/CT MRI; mesothelioma; pleural disease

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pleural Neoplasms / Deep Learning / Mesothelioma, Malignant / Mesothelioma Type of study: Guideline / Observational_studies / Prognostic_studies Limits: Humans Language: En Journal: Thorax Year: 2022 Document type: Article Affiliation country: Reino Unido Country of publication: Reino Unido

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