AIMC Topic: Deep Learning

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Deep learning approach for accurate prostate cancer identification and stratification using combined immunostaining of cytokeratin, p63, and racemase.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: Prostate cancer (PCa) is the most frequently diagnosed cancer in men worldwide, affecting around 1.4 million individuals. Current PCa diagnosis relies on histological analysis of prostate biopsy samples, an activity that is both time-cons...

Clinical evaluation of deep learning-based automatic clinical target volume segmentation: a single-institution multi-site tumor experience.

La Radiologia medica
PURPOSE: The large variability in tumor appearance and shape makes manual delineation of the clinical target volume (CTV) time-consuming, and the results depend on the oncologists' experience. Whereas deep learning techniques have allowed oncologists...

A Novel Two-Stage Induced Deep Learning System for Classifying Similar Drugs with Diverse Packaging.

Sensors (Basel, Switzerland)
Dispensing errors play a crucial role in various medical errors, unfortunately emerging as the third leading cause of death in the United States. This alarming statistic has spurred the World Health Organization (WHO) into action, leading to the init...

Screening adequacy of unstained thyroid fine needle aspiration samples using a deep learning-based classifier.

Scientific reports
Fine needle aspiration (FNA) biopsy of thyroid nodules is a safe, cost-effective, and accurate diagnostic method for detecting thyroid cancer. However, about 10% of initial FNA biopsy samples from patients are non-diagnostic and require repeated FNA,...

A Deep Learning Model Enhances Clinicians' Diagnostic Accuracy to More Than 96% for Anterior Cruciate Ligament Ruptures on Magnetic Resonance Imaging.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To develop a deep learning model to accurately detect anterior cruciate ligament (ACL) ruptures on magnetic resonance imaging (MRI) and to evaluate its effect on the diagnostic accuracy and efficiency of clinicians.

Applying deep learning to recognize the properties of vitreous opacity in ophthalmic ultrasound images.

Eye (London, England)
BACKGROUND: To explore the feasibility of artificial intelligence technology based on deep learning to automatically recognize the properties of vitreous opacities in ophthalmic ultrasound images.

Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.

International journal of computer assisted radiology and surgery
PURPOSE: The proposed work aims to develop an algorithm to precisely segment the lung parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a combination of deep learning and traditional image processing algorithms. T...

Deep Learning Model for Predicting Airway Organoid Differentiation.

Tissue engineering and regenerative medicine
BACKGROUND: Organoids are self-organized three-dimensional culture systems and have the advantages of both in vitro and in vivo experiments. However, each organoid has a different degree of self-organization, and methods such as immunofluorescence st...

Fully automated film mounting in dental radiography: a deep learning model.

BMC medical imaging
BACKGROUND: Dental film mounting is an essential but time-consuming task in dental radiography, with manual methods often prone to errors. This study aims to develop a deep learning (DL) model for accurate automated classification and mounting of bot...

Multimodality deep learning radiomics nomogram for preoperative prediction of malignancy of breast cancer: a multicenter study.

Physics in medicine and biology
. Breast cancer is the most prevalent cancer diagnosed in women worldwide. Accurately and efficiently stratifying the risk is an essential step in achieving precision medicine prior to treatment. This study aimed to construct and validate a nomogram ...