Although using standardized reports is encouraged, most emergency radiological reports in France remain in free-text format that can be mined with natural language processing for epidemiological purposes, activity monitoring or data collection. These...
Algorithms that automatically identify nodular patterns in chest X-ray (CXR) images could benefit radiologists by reducing reading time and improving accuracy. A promising approach is to use deep learning, where a deep neural network (DNN) is trained...
The external and middle ear conditions are diagnosed using a digital otoscope. The clinical diagnosis of ear conditions is suffered from restricted accuracy due to the increased dependency on otolaryngologist expertise, patient complaint, blurring of...
Analyzing spinal curvatures manually is time-consuming and tedious for clinicians, and intra-observer and inter-observer variability can affect manual measurements. In this study, we developed and evaluated the performance of an automated deep learni...
Vision-based detection and tracking of surgical instrument are attractive because it relies purely on surgical instrument already in the operating scenario. The vision knowledge of the surgical instruments is a crucial piece of topic for surgical tas...
The field of artificial intelligence (AI) in medical imaging is undergoing explosive growth, and Radiology is a prime target for innovation. The American College of Radiology Data Science Institute has identified more than 240 specific use cases wher...
Large datasets with high-quality labels required to train deep neural networks are challenging to obtain in the radiology domain. This work investigates the effect of training dataset size on the performance of deep learning classifiers, focusing on ...
Neuroblastoma is one of the most common pediatric cancers. This study used machine learning (ML) to predict the mortality and a few other investigated intermediate outcomes of neuroblastoma patients non-invasively from CT images. Performances of mult...
This study details application of deep learning for automatic segmentation of the ascending and descending aorta from 2D phase-contrast cine magnetic resonance imaging for automatic aortic analysis on the large MESA cohort with assessment on an exter...
Medical image captioning has been recently attracting the attention of the medical community. Also, generating captions for images involving multiple organs is an even more challenging task. Therefore, any attempt toward such medical image captioning...