AIMC Topic: Deep Learning

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Deep learning for mass detection in Full Field Digital Mammograms.

Computers in biology and medicine
In recent years, the use of Convolutional Neural Networks (CNNs) in medical imaging has shown improved performance in terms of mass detection and classification compared to current state-of-the-art methods. This paper proposes a fully automated frame...

Learned optical flow for intra-operative tracking of the retinal fundus.

International journal of computer assisted radiology and surgery
PURPOSE: Sustained delivery of regenerative retinal therapies by robotic systems requires intra-operative tracking of the retinal fundus. We propose a supervised deep convolutional neural network to densely predict semantic segmentation and optical f...

Perioperative margin detection in basal cell carcinoma using a deep learning framework: a feasibility study.

International journal of computer assisted radiology and surgery
PURPOSE: Basal cell carcinoma (BCC) is the most commonly diagnosed cancer and the number of diagnosis is growing worldwide due to increased exposure to solar radiation and the aging population. Reduction of positive margin rates when removing BCC lea...

Leveraging vision and kinematics data to improve realism of biomechanic soft tissue simulation for robotic surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical simulations play an increasingly important role in surgeon education and developing algorithms that enable robots to perform surgical subtasks. To model anatomy, finite element method (FEM) simulations have been held as the gold sta...

Deep learning in mental health outcome research: a scoping review.

Translational psychiatry
Mental illnesses, such as depression, are highly prevalent and have been shown to impact an individual's physical health. Recently, artificial intelligence (AI) methods have been introduced to assist mental health providers, including psychiatrists a...

A Spatiotemporal Convolutional Network for Multi-Behavior Recognition of Pigs.

Sensors (Basel, Switzerland)
The statistical data of different kinds of behaviors of pigs can reflect their health status. However, the traditional behavior statistics of pigs were obtained and then recorded from the videos through human eyes. In order to reduce labor and time c...

Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Nutrients
Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding and addressing poor dietary practices. However, diets are incredibly diverse across populations and ...

Segmentation of finger tendon and synovial sheath in ultrasound image using deep convolutional neural network.

Biomedical engineering online
BACKGROUND: Trigger finger is a common hand disease, which is caused by a mismatch in diameter between the tendon and the pulley. Ultrasound images are typically used to diagnose this disease, which are also used to guide surgical treatment. However,...

Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification.

IEEE transactions on cybernetics
Convolutional neural networks (CNNs) have gained remarkable success on many image classification tasks in recent years. However, the performance of CNNs highly relies upon their architectures. For the most state-of-the-art CNNs, their architectures a...