AIMC Topic: Neural Networks, Computer

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Integrating model explanations and hybrid priors into deep stacked networks for the "safe zone" prediction of acetabular cup.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Existing state-of-the-art "safe zone" prediction methods are statistics-based methods, image-matching techniques, and machine learning methods. Yet, those methods bring a tension between accuracy and interpretability.

Inter-Slice Resolution Improvement Using Convolutional Neural Network with Orbital Bone Edge-Aware in Facial CT Images.

Journal of digital imaging
The 3D modeling of orbital bones in facial CT images is essential to provide a customized implant for reconstructions of orbit and related structures during surgery. However, 3D models of the orbital bone show an aliasing effect and disconnected thin...

3D vessel-like structure segmentation in medical images by an edge-reinforced network.

Medical image analysis
The vessel-like structure in biomedical images, such as within cerebrovascular and nervous pathologies, is an essential biomarker in understanding diseases' mechanisms and in diagnosing and treating diseases. However, existing vessel-like structure s...

Automatic detection of three cell types in a microscope image based on deep learning.

Journal of biophotonics
With the continuous integration of deep learning and the technique of molecular biology, target detection models must accurately detect the position of each cell in the image and classify it correctly. We present a model for the multi-scale feature f...

Automated irreversible electroporated region prediction using deep neural network, a preliminary study for treatment planning.

Electromagnetic biology and medicine
The primary purpose of cancer treatment with irreversible electroporation (IRE) is to maximize tumor damage and minimize surrounding healthy tissue damage. Finite element analysis is one of the popular ways to calculate electric field and cell kill p...

Frequency, Time, Representation and Modeling Aspects for Major Speech and Audio Processing Applications.

Sensors (Basel, Switzerland)
There are many speech and audio processing applications and their number is growing. They may cover a wide range of tasks, each having different requirements on the processed speech or audio signals and, therefore, indirectly, on the audio sensors as...

Spatial point patterns generation on remote sensing data using convolutional neural networks with further statistical analysis.

Scientific reports
Continuous technological growth and the corresponding environmental implications are triggering the enhancement of advanced environmental monitoring solutions, such as remote sensing. In this paper, we propose a new method for the spatial point patte...

Study on image data cleaning method of early esophageal cancer based on VGG_NIN neural network.

Scientific reports
In order to clean the mislabeled images in the esophageal endoscopy image data set, we designed a new neural network VGG_NIN. Based on the new neural network structure, we developed a method to clean the mislabeled images in the esophageal endoscopy ...

Automated COVID-19 Classification Using Heap-Based Optimization with the Deep Transfer Learning Model.

Computational intelligence and neuroscience
The outbreak of the COVID-19 pandemic necessitates prompt identification of affected persons to restrict the spread of the COVID-19 epidemic. Radiological imaging such as computed tomography (CT) and chest X-rays (CXR) is considered an effective way ...

Atrous residual convolutional neural network based on U-Net for retinal vessel segmentation.

PloS one
Extracting features of retinal vessels from fundus images plays an essential role in computer-aided diagnosis of diseases, such as diabetes, hypertension, and cerebrovascular diseases. Although a number of deep learning-based methods have been used i...