135 citations · 175 across the 4 of their papers we have counts for
5 papers
RadVLM: A Multitask Conversational Vision-Language Model for Radiology
Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruipérez-Campillo +12
The widespread use of chest X-rays (CXRs), coupled with a shortage of radiologists, has driven growing interest in automated CXR analysis and AI-assisted reporting. While existing…
Exploring Multilingual Large Language Models for Enhanced TNM classification of Radiology Report in lung cancer staging
Hidetoshi Matsuo, Mizuho Nishio, Takaaki Matsunaga +2
Background: Structured radiology reports remains underdeveloped due to labor-intensive structuring and narrative-style reporting. Deep learning, particularly large language models…
Development of pericardial fat count images using a combination of three different deep-learning models
Takaaki Matsunaga, Atsushi Kono, Hidetoshi Matsuo +9
Rationale and Objectives: Pericardial fat (PF), the thoracic visceral fat surrounding the heart, promotes the development of coronary artery disease by inducing inflammation of the…
Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks
Hidetoshi Matsuo, Mizuho Nishio, Munenobu Nogami +6
The integrated positron emission tomography/magnetic resonance imaging (PET/MRI) scanner facilitates the simultaneous acquisition of metabolic information via PET and morphological…
Automatic classification between COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy on chest X-ray image: combination of data augmentation methods
Mizuho Nishio, Shunjiro Noguchi, Hidetoshi Matsuo +1
Purpose: This study aimed to develop and validate computer-aided diagnosis (CXDx) system for classification between COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy on c…