• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1486-1495
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• 2020

The analysis of digital microscopy images plays a vital role in computer-aided diagnosis (CAD) and prognosis. The main purpose of this paper is to develop a machine learning technique to predict the histological grades in prostate biopsy. To perform a multiclass classification, an AI-based deep learning algorithm, a multichannel convolutional neural network (MCCNN) was developed by connecting layers with artificial neurons inspired by the human brain system. The histological grades that were used for the analysis are benign, grade 3, grade 4, and grade 5. The proposed approach aims to classify multiple patterns of images extracted from the whole slide image (WSI) of a prostate biopsy based on the Gleason grading system. The Multichannel Convolution Neural Network (MCCNN) model takes three input channels (Red, Green, and Blue) to extract the computational features from each channel and concatenate them for multiclass classification. Stain normalization was carried out for each histological grade to standardize the intensity and contrast level in the image. The proposed model has been trained, validated, and tested with the histopathological images and has achieved an average accuracy of 96.4%, 94.6%, and 95.1%, respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.97-106
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• 2022

In this study, H&E staining is necessary to distinguish cells. However, dyeing directly requires a lot of money and time. The purpose is to convert the phase image of unstained cells to the amplitude image of stained cells. Image data taken with FPM was created with Phase image and Amplitude image using Matlab's parameters. Through normalization, a visually identifiable image was obtained. Through normalization, a visually distinguishable image was obtained. Using the GAN algorithm, a Fake Amplitude image similar to the Real Amplitude image was created based on the Phase image, and cells were distinguished by objectification using MASK R-CNN with the Fake Amplitude image As a result of the study, D loss max is 3.3e-1, min is 6.8e-2, G loss max is 6.9e-2, min is 2.9e-2, A loss max is 5.8e-1, min is 1.2e-1, Mask R-CNN max is 1.9e0, and min is 3.2e-1.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.22 no.2
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• pp.155-163
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• 2000

Osteoporosis is the consequence of an imbalance between osteoclastic and osteoblastic activity, coupled with an increased rate of bone turnover observed with menopause. Estrogen is generally considered to maintain bone mass through suppression of bone resorption. The purpose of this study was to evaluate the rat femoral trabecular change not only in the deficiency of estrogen but also in the administration of estrogen following ovariectomy(OVX). 30 female Sprague-Dawley rats were subjected to bilateral OVX or sham surgery(control). Groups of OVX were divided into 4 groups. The first group was injected daily with vehicle alone for 20 days after 20 weeks following OVX. The additional groups of OVX was injected daily with low, medium, or high doses of $17{\beta}-estradiol$(10, 25 or $50{\mu}g/kg$ BW, respectively). All rats were sacrified 23 weeks after OVX, and their femur were processed for H&E, MT stain and histomorphometry. The results were as follows; 1. In the histomorphometric analysis, the trabecular bone volume/tissue volume, trabecular thickness and trabecular seperation were respectively $31.2{\pm}8.3%$, $54.3{\pm}4.8{\mu}m$ and $280.7{\pm}16.4{\mu}m$ in vehicle treated OVX group and $48.6{\pm}7.3%$, $90.4{\pm}4.5{\mu}m$ and $126.3{\pm}5{\mu}m$ in sham operation group, and they showed statistical significance compare to control group. 2. The trabecular bone volume/tissue volume, trabecular thickness and trabecular separation were respectively $44.4{\pm}4.3%$, $109.5{\pm}12.3{\mu}m$ and $94.9{\pm}8.5{\mu}m$ in low doses of $17{\beta}-estradiol$ injected group and they showed statistical significance compare to OVX group. 3. The trabecular bone volume/tissue volume, trabecular thickness and trabecular separation were respectively $44.4{\pm}4.3%$, $109.5{\pm}12.3{\mu}m$ and $94.9{\pm}8.5{\mu}m$ in medium doses of $17{\beta}-estradiol$ injected group and they showed statistical significance compare to OVX group, but they didn't show statistical significance compare to low doses of $17{\beta}-estradiol$ injected group. 4. The trabecular bone volume/tissue volume, trabecular thickness and trabecular separation were respectively $46.4{\pm}4.5%$, $154.4{\pm}13.2{\mu}m$ and $113.7{\pm}12.8{\mu}m$ in high doses of $17{\beta}-estradiol$ injected group and they also showed statistical significance compare to OVX group, but they didn't show statistical significance compare to other experimental groups. From the above results, metaphyseal bone formation was markedly reduced in OVX rate but treatment of OVX rats with $17{\beta}-estradiol$ resulted in normalization of femur trabecular bone volume. But they didn't show statistical significance the effect of bone formation according to the dose dependency.