AIMC Topic: Image Processing, Computer-Assisted

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MP-Net: Deep learning-based segmentation for fluorescence microscopy images of microplastics isolated from clams.

PloS one
Environmental monitoring of microplastics (MP) contamination has become an area of great research interest, given potential hazards associated with human ingestion of MP. In this context, determination of MP concentration is essential. However, cheap...

Protocol for live cell image segmentation to profile cellular morphodynamics using MARS-Net.

STAR protocols
Quantitative studies of cellular morphodynamics rely on accurate cell segmentation in live cell images. However, fluorescence and phase contrast imaging hinder accurate edge localization. To address this challenge, we developed MARS-Net, a deep learn...

Deep learning based domain adaptation for mitochondria segmentation on EM volumes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate segmentation of electron microscopy (EM) volumes of the brain is essential to characterize neuronal structures at a cell or organelle level. While supervised deep learning methods have led to major breakthroughs in ...

Editorial of Special Issue "Deep Learning and Machine Learning in Bioinformatics".

International journal of molecular sciences
In recent years, deep learning has emerged as a highly active research field, achieving great success in various machine learning areas, including image processing, speech recognition, and natural language processing, and now rapidly becoming a domin...

An Enhanced Priori Knowledge GAN for CT Images Generation of Early Lung Nodules with Small-Size Labelled Samples.

Oxidative medicine and cellular longevity
The small size of labelled samples is one of the challenging problems in identifying early lung nodules from CT images using deep learning methods. Recent literature on the topic shows that deep convolutional generative adversarial network (DCGAN) ha...

EPI phase error correction with deep learning (PEC-DL) at 7 T.

Magnetic resonance in medicine
PURPOSE: The phase mismatch between odd and even echoes in EPI causes Nyquist ghost artifacts. Existing ghost correction methods often suffer from severe residual artifacts and are ineffective with k-space undersampling data. This study proposed a de...

Multiple-Attention Mechanism Network for Semantic Segmentation.

Sensors (Basel, Switzerland)
Contextual information and the dependencies between dimensions is vital in image semantic segmentation. In this paper, we propose a multiple-attention mechanism network (MANet) for semantic segmentation in a very effective and efficient way. Concrete...

Beyond automatic medical image segmentation-the spectrum between fully manual and fully automatic delineation.

Physics in medicine and biology
Semi-automatic and fully automatic contouring tools have emerged as an alternative to fully manual segmentation to reduce time spent contouring and to increase contour quality and consistency. Particularly, fully automatic segmentation has seen excep...

Artificial Intelligence-Based Semisupervised Self-Training Algorithm in Pathological Tissue Image Segmentation.

Computational intelligence and neuroscience
In the field of medical image processing, due to the differences in tissues, organs, and imaging methods, obtained medical images have significant differences. With the development of intelligence in medicine, an increasing number of computing optimi...

The Psychological Education Strategy of Music Generation and Creation by Generative Confrontation Network under Deep Learning.

Computational intelligence and neuroscience
In order to study the role of generative adversarial network (GAN) in music generation, this article creates a convolutional GAN-based Midinet as a baseline model through the music generation process and creative psychological education and GAN princ...