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RECOMIA invites nuclear medicine specialists, radiologists, technologists, physicists and others interested in AI and medical imaging to participate in our projects.
All participants get one month free access to the e-learning site eScan Academy when the project is finished.
Are you part of a research group? Are you interested in AI in medical imaging? Do you want to apply our AI-based tools to your data?
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Four abstracts have been accepted as oral presentations at the upcoming European Congress of Radiology 2020, March 11-15 in Vienna, Austria. More information will come.
Two abstracts at the Radiological Society of North America (RSNA) 2019 Scientific Assembly and Annual Meeting, December 1 - December 6, 2019, Chicago are based on the RECOMIA platform:
Automatic Acquired 18F-Choline PET/CT Biomarkers Association with Prognostic Value in High-Risk Prostate Cancer Patients. Borrelli,P, Kjolhede,H, Enqvist,O, Polymeri,E, Ohlsson,M, Tragardh,E, Edenbrandt,L. Oral presentation
Deep Learning Takes the Pain Out of Back Breaking Work - Automatic Vertebral Segmentation and Attenuation Measurement for Opportunistic Osteoporosis Screening. Schmidt,D, Enqvist,O, Ulen,J, Persson,E, Tragardh,E, Leander,P, Edenbrandt,L. Poster presentation
Deep learning‐based quantification of PET/CT prostate gland uptake: association with overall survival. Polymeri E, Sadik M, Kaboteh R, Borrelli P, Enqvist O, Ulén J, Ohlsson M, Trägårdh E, Poulsen MH, Simonsen JA, Hoilund-Carlsen PF, Johnsson ÅA, Edenbrandt L. Clin Physiol Funct Imaging. 2019; Dec 3. doi: 10.1111/cpf.12611[Epub ahead of print]
Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study. Mortensen MA, Borrelli P, Poulsen MH, Gerke O, Enqvist O, Ulén J, Trägårdh E, Constantinescu C, Edenbrandt L, Lund L, Høilund-Carlsen PF. Clin Physiol Funct Imaging. 2019:39;399-406.
Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases. Lindgren Belal S, Sadik M, Kaboteh R, Enqvist O, Ulén J, Poulsen MH, Simonsen J, Høilund-Carlsen PF, Edenbrandt L, Trägårdh E. Eur J Radiol 2019;113:89-95.