AIMC Topic: Pattern Recognition, Automated

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Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images.

Medical image analysis
The goal of this work was to develop a method for accurate and robust automatic segmentation of the prostate clinical target volume in transrectal ultrasound (TRUS) images for brachytherapy. These images can be difficult to segment because of weak or...

Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces.

Medical image analysis
Classical deformable registration techniques achieve impressive results and offer a rigorous theoretical treatment, but are computationally intensive since they solve an optimization problem for each image pair. Recently, learning-based methods have ...

Using a deep learning system in endoscopy for screening of early esophageal squamous cell carcinoma (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Few artificial intelligence-based technologies have been developed to improve the efficiency of screening for esophageal squamous cell carcinoma (ESCC). Here, we developed and validated a novel system of computer-aided detection ...

AMC-Net: Asymmetric and multi-scale convolutional neural network for multi-label HPA classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The multi-label Human Protein Atlas (HPA) classification can yield a better understanding of human diseases and help doctors to enhance the automatic analysis of biomedical images. The existing automatic protein recognition...

An Improved Convolutional Neural Network Algorithm and Its Application in Multilabel Image Labeling.

Computational intelligence and neuroscience
In today's society, image resources are everywhere, and the number of available images can be overwhelming. Determining how to rapidly and effectively query, retrieve, and organize image information has become a popular research topic, and automatic ...

When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time.

Neural computation
A significant threat to the recent, wide deployment of machine learning-based systems, including deep neural networks (DNNs), is adversarial learning attacks. The main focus here is on evasion attacks against DNN-based classifiers at test time. While...

Automatic recognition of different types of acute leukaemia in peripheral blood by image analysis.

Journal of clinical pathology
AIMS: Morphological differentiation among different blast cell lineages is a difficult task and there is a lack of automated analysers able to recognise these abnormal cells. This study aims to develop a machine learning approach to predict the diagn...

Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Wheezing is a common symptom of patients caused by asthma and chronic obstructive pulmonary diseases. Wheezing detection identifies wheezing lung sounds and helps physicians in diagnosis, monitoring, and treatment of pulmona...

Adaptive Learning Emotion Identification Method of Short Texts for Online Medical Knowledge Sharing Community.

Computational intelligence and neuroscience
The medical knowledge sharing community provides users with an open platform for accessing medical resources and sharing medical knowledge, treatment experience, and emotions. Compared with the recipients of general commodities, the recipients in the...

Adaptive Global Sliding-Mode Control for Dynamic Systems Using Double Hidden Layer Recurrent Neural Network Structure.

IEEE transactions on neural networks and learning systems
In this paper, a full-regulated neural network (NN) with a double hidden layer recurrent neural network (DHLRNN) structure is designed, and an adaptive global sliding-mode controller based on the DHLRNN is proposed for a class of dynamic systems. The...