AIMC Topic: Image Processing, Computer-Assisted

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Mini Review: The Last Mile-Opportunities and Challenges for Machine Learning in Digital Toxicologic Pathology.

Toxicologic pathology
The 2019 manuscript by the Special Interest Group on Digital Pathology and Image Analysis of the Society of Toxicologic pathology suggested that a synergism between artificial intelligence (AI) and machine learning (ML) technologies and digital toxic...

Learning to map 2D ultrasound images into 3D space with minimal human annotation.

Medical image analysis
In fetal neurosonography, aligning two-dimensional (2D) ultrasound scans to their corresponding plane in the three-dimensional (3D) space remains a challenging task. In this paper, we propose a convolutional neural network that predicts the position ...

CASSPER is a semantic segmentation-based particle picking algorithm for single-particle cryo-electron microscopy.

Communications biology
Particle identification and selection, which is a prerequisite for high-resolution structure determination of biological macromolecules via single-particle cryo-electron microscopy poses a major bottleneck for automating the steps of structure determ...

Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI.

BMC medical imaging
BACKGROUND: Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only ...

Hyperspectral prediction of sugarbeet seed germination based on gauss kernel SVM.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
How to quickly and accurately select sugarbeet seeds with reliable germination is very important to sugarbeet planting. In this study, the hyperspectral images of 3072 sugarbeet seeds of the same variety were collected, and were successively processe...

Improved deep CNNs based on Nonlinear Hybrid Attention Module for image classification.

Neural networks : the official journal of the International Neural Network Society
Recent years have witnessed numerous successful applications of incorporating attention module into feed-forward convolutional neural networks. Along this line of research, we design a novel lightweight general-purpose attention module by simultaneou...

DeepHCS: Bright-field to fluorescence microscopy image conversion using multi-task learning with adversarial losses for label-free high-content screening.

Medical image analysis
In this paper, we propose a novel microscopy image translation method for transforming a bright-field microscopy image into three different fluorescence images to observe the apoptosis, nuclei, and cytoplasm of cells, which visualize dead cells, nucl...

GroupRegNet: a groupwise one-shot deep learning-based 4D image registration method.

Physics in medicine and biology
Accurate deformable four-dimensional (4D) (three-dimensional in space and time) medical images registration is essential in a variety of medical applications. Deep learning-based methods have recently gained popularity in this area for the significan...

Unsupervised Cross Domain Person Re-Identification by Multi-Loss Optimization Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Unsupervised cross domain (UCD) person re-identification (re-ID) aims to apply a model trained on a labeled source domain to an unlabeled target domain. It faces huge challenges as the identities have no overlap between these two domains. At present,...