• 제목/요약/키워드: Stain Normalization

검색결과 3건 처리시간 0.019초

Multichannel Convolution Neural Network Classification for the Detection of Histological Pattern in Prostate Biopsy Images

  • Bhattacharjee, Subrata;Prakash, Deekshitha;Kim, Cho-Hee;Choi, Heung-Kook
    • 한국멀티미디어학회논문지
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    • 제23권12호
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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.

Fourier Ptychographic Microscopy 영상에서의 딥러닝 기반 디지털 염색 방법 연구 (Deep Learning Based Digital Staining Method in Fourier Ptychographic Microscopy Image)

  • 황석민;김동범;김유정;김여린;이종하
    • 융합신호처리학회논문지
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    • 제23권2호
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    • pp.97-106
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    • 2022
  • 본 연구에서 세포를 분별하기 위해 H&E 염색이 필요하다. 그러나 직접 염색하면 많은 비용과 시간이 필요하다. H&E 염색되지 않은 세포의 Phase image에서 H&E 염색이 된 세포의 Amplitude image로 변환 하는 것이 목적이다. FPM으로 촬영한 Image data를 가지고 Matlab을 이용해 매개변수를 변경해 Phase image와 Amplitude image를 만들었다. 정규화를 통해 육안으로 식별이 가능한 이미지를 얻었다. GAN 알고리즘을 이용해 Phase image를 기반으로 Real Amplitude image와 비슷한 Fake Amplitude image를 만들고 Fake Amplitude image를 가지고 MASK R-CNN을 이용하여 세포를 분별하여 객체화를 통해 구분했다. 연구 결과 D loss의 max는 3.3e-1, min은 6.8e-2, G loss max는 6.9e-2, min은 2.9e-2, A loss는 max 5.8e-1, min은 1.2e-1, Mask R-CNN max는 1.9e0, min은 3.2e-1이다.

난소 절제된 백서에서 에스트로젠 투여용량에 따른 대퇴골주 변화에 대한 연구 (A Study on the trabecular change of Femur according to $17{\beta}-Estradiol$ Dosage in Ovariectomized Rat)

  • 김성주;김경욱;이재훈
    • Maxillofacial Plastic and Reconstructive Surgery
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    • 제22권2호
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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.

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