AIMC Topic: Image Processing, Computer-Assisted

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A Survey of Deep Convolutional Neural Networks Applied for Prediction of Plant Leaf Diseases.

Sensors (Basel, Switzerland)
In the modern era, deep learning techniques have emerged as powerful tools in image recognition. Convolutional Neural Networks, one of the deep learning tools, have attained an impressive outcome in this area. Applications such as identifying objects...

Deep learning for COVID-19 detection based on CT images.

Scientific reports
COVID-19 has tremendously impacted patients and medical systems globally. Computed tomography images can effectively complement the reverse transcription-polymerase chain reaction testing. This study adopted a convolutional neural network for COVID-1...

BCDnet: Parallel heterogeneous eight-class classification model of breast pathology.

PloS one
Breast cancer is the cancer with the highest incidence of malignant tumors in women, which seriously endangers women's health. With the help of computer vision technology, it has important application value to automatically classify pathological tiss...

A Two-Stream Dynamic Pyramid Representation Model for Video-Based Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Video-based person re-identification (Re-ID) leverages rich spatio-temporal information embedded in sequence data to further improve the retrieval accuracy comparing with single image Re-ID. However, it also brings new difficulties. 1) Both spatial a...

Human Interaction Understanding With Joint Graph Decomposition and Node Labeling.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The task of human interaction understanding involves both recognizing the action of each individual in the scene and decoding the interaction relationship among people, which is useful to a series of vision applications such as camera surveillance, v...

Deep Learning Network for Segmentation of the Prostate Gland With Median Lobe Enlargement in T2-weighted MR Images: Comparison With Manual Segmentation Method.

Current problems in diagnostic radiology
PURPOSE: Aim of this study was to evaluate a fully automated deep learning network named Efficient Neural Network (ENet) for segmentation of prostate gland with median lobe enlargement compared to manual segmentation.

Using neural networks to extend cropped medical images for deformable registration among images with differing scan extents.

Medical physics
PURPOSE: Missing or discrepant imaging volume is a common challenge in deformable image registration (DIR). To minimize the adverse impact, we train a neural network to synthesize cropped portions of head and neck CT's and then test its use in DIR.

Rapid high-quality PET Patlak parametric image generation based on direct reconstruction and temporal nonlocal neural network.

NeuroImage
Parametric imaging based on dynamic positron emission tomography (PET) has wide applications in neurology. Compared to indirect methods, direct reconstruction methods, which reconstruct parametric images directly from the raw PET data, have superior ...

Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. I...

Efficient Source Camera Identification with Diversity-Enhanced Patch Selection and Deep Residual Prediction.

Sensors (Basel, Switzerland)
Source camera identification has long been a hot topic in the field of image forensics. Besides conventional feature engineering algorithms developed based on studying the traces left upon shooting, several deep-learning-based methods have also emerg...