AIMC Topic: Humans

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Automated Detection of Epiretinal Membranes in OCT Images Using Deep Learning.

Ophthalmic research
INTRODUCTION: Development and validation of a deep learning algorithm to automatically identify and locate epiretinal memberane (ERM) regions in OCT images.

An uncertainty-aware deep learning architecture with outlier mitigation for prostate gland segmentation in radiotherapy treatment planning.

Medical physics
PURPOSE: Task automation is essential for efficient and consistent image segmentation in radiation oncology. We report on a deep learning architecture, comprising a U-Net and a variational autoencoder (VAE) for automatic contouring of the prostate gl...

DuDoSS: Deep-learning-based dual-domain sinogram synthesis from sparsely sampled projections of cardiac SPECT.

Medical physics
PURPOSE: Myocardial perfusion imaging (MPI) using single-photon emission-computed tomography (SPECT) is widely applied for the diagnosis of cardiovascular diseases. In clinical practice, the long scanning procedures and acquisition time might induce ...

T-SPOT with CT image analysis based on deep learning for early differential diagnosis of nontuberculous mycobacteria pulmonary disease and pulmonary tuberculosis.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
OBJECTIVES: This study aimed to establish a diagnostic algorithm combining T-SPOT with computed tomography image analysis based on deep learning (DL) for early differential diagnosis of nontuberculous mycobacteria pulmonary disease (NTM-PD) and pulmo...

Current Status of Objectification of Four Diagnostic Methods on Constitution Recognition of Chinese Medicine.

Chinese journal of integrative medicine
Chinese medicine (CM) has thousands of years of experience in prevention of diseases. As for CM, people's constitution is closely related to their health status, thus recognition of CM constitution is the fundamental and core content of research on c...

AIMIC: Deep Learning for Microscopic Image Classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning techniques are powerful tools for image analysis. However, the lack of programming experience makes it difficult for novice users to apply this technology. This project aims to lower the barrier for clinical us...

Radiomics in neuro-oncological clinical trials.

The Lancet. Digital health
The development of clinical trials has led to substantial improvements in the prevention and treatment of many diseases, including brain cancer. Advances in medicine, such as improved surgical techniques, the development of new drugs and devices, the...

Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal data.

Surgical endoscopy
BACKGROUND: Personalized medicine requires the integration and analysis of vast amounts of patient data to realize individualized care. With Surgomics, we aim to facilitate personalized therapy recommendations in surgery by integration of intraoperat...

Automatic lung tumor segmentation from CT images using improved 3D densely connected UNet.

Medical & biological engineering & computing
Accurate lung tumor segmentation has great significance in the treatment planning of lung cancer. However, robust lung tumor segmentation becomes challenging due to the heterogeneity of tumors and the similar visual characteristics between tumors and...

Assessment of an artificial intelligence aid for the detection of appendicular skeletal fractures in children and young adults by senior and junior radiologists.

Pediatric radiology
BACKGROUND: As the number of conventional radiographic examinations in pediatric emergency departments increases, so, too, does the number of reading errors by radiologists.