AIMC Topic: Microscopy

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A Transfer Learning Based Super-Resolution Microscopy for Biopsy Slice Images: The Joint Methods Perspective.

IEEE/ACM transactions on computational biology and bioinformatics
Higher-resolution biopsy slice images reveal many details, which are widely used in medical practice. However, taking high-resolution slice images is more costly than taking low-resolution ones. In this paper, we propose a joint framework containing ...

Spherical-Patches Extraction for Deep-Learning-Based Critical Points Detection in 3D Neuron Microscopy Images.

IEEE transactions on medical imaging
Digital reconstruction of neuronal structures is very important to neuroscience research. Many existing reconstruction algorithms require a set of good seed points. 3D neuron critical points, including terminations, branch points and cross-over point...

A Curvature-Enhanced Random Walker Segmentation Method for Detailed Capture of 3D Cell Surface Membranes.

IEEE transactions on medical imaging
High-resolution 3D microscopy is a fast advancing field and requires new techniques in image analysis to handle these new datasets. In this work, we focus on detailed 3D segmentation of Dictyostelium cells undergoing macropinocytosis captured on an i...

Deep Learning for Imaging and Detection of Microorganisms.

Trends in microbiology
Despite tremendous recent interest, the application of deep learning in microbiology has still not reached its full potential. To tackle the challenges faced by human-operated microscopy, deep-learning-based methods have been proposed for microscopic...

Evaluation and development of deep neural networks for image super-resolution in optical microscopy.

Nature methods
Deep neural networks have enabled astonishing transformations from low-resolution (LR) to super-resolved images. However, whether, and under what imaging conditions, such deep-learning models outperform super-resolution (SR) microscopy is poorly expl...

Robust Mosaicing of Endomicroscopic Videos via Context-Weighted Correlation Ratio.

IEEE transactions on bio-medical engineering
Probe-based confocal laser endomicroscopy (pCLE) is a promising imaging tool that provides in situ and in vivo optical imaging to perform real-time pathological assessments. However, due to limited field of view, it is difficult for clinicians to get...

Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label-Free Multiphoton Microscopy Using Convolutional Neural Networks.

Lasers in surgery and medicine
BACKGROUND AND OBJECTIVES: Histological analysis is a gold standard technique for studying impaired skin wound healing. Label-free multiphoton microscopy (MPM) can provide natural image contrast similar to histological sections and quantitative metab...

Light microscopic iris classification using ensemble multi-class support vector machine.

Microscopy research and technique
Similar to other biometric systems such as fingerprint, face, DNA, iris classification could assist law enforcement agencies in identifying humans. Iris classification technology helps law-enforcement agencies to recognize humans by matching their ir...

A deep learning approach to the screening of malaria infection: Automated and rapid cell counting, object detection and instance segmentation using Mask R-CNN.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate and early diagnosis is critical to proper malaria treatment and hence death prevention. Several computer vision technologies have emerged in recent years as alternatives to traditional microscopy and rapid diagnostic tests. In this work, we ...

Quantitative analysis of blood cells from microscopic images using convolutional neural network.

Medical & biological engineering & computing
Blood cell count provides relevant clinical information about different kinds of disorders. Any deviation in the number of blood cells implies the presence of infection, inflammation, edema, bleeding, and other blood-related issues. Current microscop...