AIMC Topic: Deep Learning

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Automated Detection Model Based on Deep Learning for Knee Joint Motion Injury due to Martial Arts.

Computational and mathematical methods in medicine
OBJECTIVE: Develop a set of knee joint martial arts injury monitoring models based on deep learning, train and evaluate the model's effectiveness.

A Novel Deep Learning Network and Its Application for Pulmonary Nodule Segmentation.

Computational intelligence and neuroscience
Pulmonary nodules are the early manifestation of lung cancer, which appear as circular shadow of no more than 3 cm on the computed tomography (CT) image. Accurate segmentation of the contours of pulmonary nodules can help doctors improve the efficien...

Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Automatic segmentation has recently been developed to yield objective data. Prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using radiomics has been reported.

A Deep Learning Model for Classification of Parotid Neoplasms Based on Multimodal Magnetic Resonance Image Sequences.

The Laryngoscope
OBJECTIVE: To design a deep learning model based on multimodal magnetic resonance image (MRI) sequences for automatic parotid neoplasm classification, and to improve the diagnostic decision-making in clinical settings.

Tackling the class imbalance problem of deep learning-based head and neck organ segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: The segmentation of organs at risk (OAR) is a required precondition for the cancer treatment with image- guided radiation therapy. The automation of the segmentation task is therefore of high clinical relevance. Deep learning (DL)-based medi...

Detection of adulteration in mutton using digital images in time domain combined with deep learning algorithm.

Meat science
A novel method based on digital images in time domain combined with convolutional neural network (CNN) is proposed for discrimination and analysis of the adulterated mutton. For this, 195 sample images during the constant temperature heating process ...

Automatic characterization of human embryos at day 4 post-insemination from time-lapse imaging using supervised contrastive learning and inductive transfer learning techniques.

Computer methods and programs in biomedicine
BACKGROUND: Embryo morphology is a predictive marker for implantation success and ultimately live births. Viability evaluation and quality grading are commonly used to select the embryo with the highest implantation potential. However, the traditiona...

A Deep-Learning-Assisted On-Mask Sensor Network for Adaptive Respiratory Monitoring.

Advanced materials (Deerfield Beach, Fla.)
Wearable respiratory monitoring is a fast, non-invasive, and convenient approach to provide early recognition of human health abnormalities like restrictive and obstructive lung diseases. Here, a computational fluid dynamics assisted on-mask sensor n...

Research on Deep Learning Automatic Vehicle Recognition Algorithm Based on RES-YOLO Model.

Sensors (Basel, Switzerland)
With the introduction of concepts such as ubiquitous mapping, mapping-related technologies are gradually applied in autonomous driving and target recognition. There are many problems in vision measurement and remote sensing, such as difficulty in aut...