AI Medical Compendium Journal:
Journal of biophotonics

Showing 81 to 90 of 107 articles

Machine learning of diffraction image patterns for accurate classification of cells modeled with different nuclear sizes.

Journal of biophotonics
Measurement of nuclear-to-cytoplasm (N:C) ratios plays an important role in detection of atypical and tumor cells. Yet, current clinical methods rely heavily on immunofluroescent staining and manual reading. To achieve the goal of rapid and label-fre...

Deep learning a boon for biophotonics?

Journal of biophotonics
This review covers original articles using deep learning in the biophotonic field published in the last years. In these years deep learning, which is a subset of machine learning mostly based on artificial neural network geometries, was applied to a ...

Portable deep learning singlet microscope.

Journal of biophotonics
Having the least lenses, the significant feature of the singlet imaging system, helps the development of the portable and cost-effective microscopes. A novel method of monochromatic/color singlet microscopy, which is combined with only one aspheric l...

Determination of causes of death via spectrochemical analysis of forensic autopsies-based pulmonary edema fluid samples with deep learning algorithm.

Journal of biophotonics
This study investigated whether infrared spectroscopy combined with a deep learning algorithm could be a useful tool for determining causes of death by analyzing pulmonary edema fluid from forensic autopsies. A newly designed convolutional neural net...

Liver tissue classification of en face images by fractal dimension-based support vector machine.

Journal of biophotonics
Full-field optical coherence tomography (FF-OCT) has been reported with its label-free subcellular imaging performance. To realize quantitive cancer detection, the support vector machine model of classifying normal and cancerous human liver tissue is...

A new deep learning method for image deblurring in optical microscopic systems.

Journal of biophotonics
Deconvolution is the most commonly used image processing method in optical imaging systems to remove the blur caused by the point-spread function (PSF). While this method has been successful in deblurring, it suffers from several disadvantages, such ...

Deep learning of diffraction image patterns for accurate classification of five cell types.

Journal of biophotonics
Development of label-free methods for accurate classification of cells with high throughput can yield powerful tools for biological research and clinical applications. We have developed a deep neural network of DINet for extracting features from cros...

Classifying T cell activity in autofluorescence intensity images with convolutional neural networks.

Journal of biophotonics
The importance of T cells in immunotherapy has motivated developing technologies to improve therapeutic efficacy. One objective is assessing antigen-induced T cell activation because only functionally active T cells are capable of killing the desired...

Epithelium segmentation and automated Gleason grading of prostate cancer via deep learning in label-free multiphoton microscopic images.

Journal of biophotonics
In the current clinical care practice, Gleason grading system is one of the most powerful prognostic predictors for prostate cancer (PCa). The grading system is based on the architectural pattern of cancerous epithelium in histological images. Howeve...

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction.

Journal of biophotonics
The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance...