AIMC Topic: Diagnostic Imaging

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In-line particle size measurement during granule fluidization using convolutional neural network-aided process imaging.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
This paper presents a machine learning-based image analysis method to monitor the particle size distribution of fluidized granules. The key components of the direct imaging system are a rigid fiber-optic endoscope, a light source and a high-speed cam...

Automated chronic wounds medical assessment and tracking framework based on deep learning.

Computers in biology and medicine
Chronic wounds are a latent health problem worldwide, due to high incidence of diseases such as diabetes and Hansen. Typically, wound evolution is tracked by medical staff through visual inspection, which becomes problematic for patients in rural are...

Semisupervised Deep Learning for the Detection of Foreign Materials on Poultry Meat with Near-Infrared Hyperspectral Imaging.

Sensors (Basel, Switzerland)
A novel semisupervised hyperspectral imaging technique was developed to detect foreign materials (FMs) on raw poultry meat. Combining hyperspectral imaging and deep learning has shown promise in identifying food safety and quality attributes. However...

Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary.

Haematologica
Deep learning (DL) is a subdomain of artificial intelligence algorithms capable of automatically evaluating subtle graphical features to make highly accurate predictions, which was recently popularized in multiple imaging-related tasks. Because of it...

Semi-Selective Array for the Classification of Purines with Surface Plasmon Resonance Imaging and Deep Learning Data Analysis.

ACS sensors
In process analytics or environmental monitoring, the real-time recording of the composition of complex samples over a long period of time presents a great challenge. Promising solutions are label-free techniques such as surface plasmon resonance (SP...

Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application.

Seminars in cancer biology
Radiomics is the extraction of predefined mathematic features from medical images for predicting variables of clinical interest. Recent research has demonstrated that radiomics can be processed by artificial intelligence algorithms to reveal complex ...

Investigating the impact of cognitive biases in radiologists' image interpretation: A scoping review.

European journal of radiology
RATIONALE AND OBJECTIVE: Image interpretation is a fundamental aspect of radiology. The treatment and management of patients relies on accurate and timely imaging diagnosis. However, errors in radiological reports can negatively impact on patient hea...

Use of Artificial Intelligence in Radiology: Impact on Pediatric Patients, a White Paper From the ACR Pediatric AI Workgroup.

Journal of the American College of Radiology : JACR
In this white paper, the ACR Pediatric AI Workgroup of the Commission on Informatics educates the radiology community about the health equity issue of the lack of pediatric artificial intelligence (AI), improves the understanding of relevant pediatri...

Deploying Artificial Intelligence for Thoracic Imaging Around the World.

Journal of the American College of Radiology : JACR
PURPOSE: Artificial intelligence (AI) thoracic imaging applications are increasingly being deployed in low- and middle-income countries (LMICs). Radiologists have a critical gatekeeping role to ensure the effective and ethical implementation of AI so...