Alain Luciani
Researcher / author (OpenAlex)
Facts
2 properties- Affiliation
- French National Institute of Health and Medical Research, Paris 12 University, University of Paris-Est, Centre hospitalier Henri Mondor, Assistance Publique – Hôpitaux de Parisas of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
- ORCID iD
- 0000-0003-0331-9474
- OpenAlex ID
- A5007684263, A5125589277as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 13
Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment,
Automated CT LI-RADS v2018 scoring of liver observations using machine learning: A multivendor, multicentre retrospective study,
Chest <scp>PET</scp>/<scp>MRI</scp> in Solid Cancers: Comparing the Diagnostic Performance of a Free‐Breathing <scp>3D‐T1‐GRE</scp> Stack‐of‐Stars Volume Interpolated Breath‐Hold Examination (<scp>StarVIBE</scp>) Acquisition With That of a <scp>3D‐T1‐GRE</scp> Volume Interpolated Breath‐Hold Examination (<scp>VIBE</scp>) for Chest Staging During Whole‐Body <scp>PET</scp>/<scp>MRI</scp>,
Detection and characterization of pancreatic lesion with artificial intelligence: The SFR 2023 artificial intelligence data challenge,
Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution,
Diagnosis of focal liver lesions from ultrasound using deep learning,
Fast T2-weighted liver MRI: Image quality and solid focal lesions conspicuity using a deep learning accelerated single breath-hold HASTE fat-suppressed sequence,
Generative adversarial networks (GAN)-based data augmentation of rare liver cancers: The SFR 2021 Artificial Intelligence Data Challenge
+5 more
← Authored by 13
Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment,
Automated CT LI-RADS v2018 scoring of liver observations using machine learning: A multivendor, multicentre retrospective study,
Chest <scp>PET</scp>/<scp>MRI</scp> in Solid Cancers: Comparing the Diagnostic Performance of a Free‐Breathing <scp>3D‐T1‐GRE</scp> Stack‐of‐Stars Volume Interpolated Breath‐Hold Examination (<scp>StarVIBE</scp>) Acquisition With That of a <scp>3D‐T1‐GRE</scp> Volume Interpolated Breath‐Hold Examination (<scp>VIBE</scp>) for Chest Staging During Whole‐Body <scp>PET</scp>/<scp>MRI</scp>,
Detection and characterization of pancreatic lesion with artificial intelligence: The SFR 2023 artificial intelligence data challenge,
Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution,
Diagnosis of focal liver lesions from ultrasound using deep learning,
Fast T2-weighted liver MRI: Image quality and solid focal lesions conspicuity using a deep learning accelerated single breath-hold HASTE fat-suppressed sequence,
Generative adversarial networks (GAN)-based data augmentation of rare liver cancers: The SFR 2021 Artificial Intelligence Data Challenge
+5 more
Affiliated with 9
French National Institute of Health and Medical Research,
Paris 12 University,
Assistance Publique – Hôpitaux de Paris,
University of Paris-Est,
Hôpital Albert-Chenevier,
University hospital of Henri-Mondor,
Biotherapy of Genetic Diseases, Inflammatory Disorders and Cancers,
Centre hospitalier Henri Mondor
+1 more
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Summary
Alain Luciani is a human[1].