Wyniki wyszukiwania - BazTech

1

SVIA dataset: A new dataset of microscopic videos and images for computer-aided sperm analysis

Chen Ao, Li Chen, Zou Shuojia, Rahaman Md Mamunur, Yao Yudong, Chen Haoyuan, Yang Hechen, Zhao Peng, Hu Weiming, Liu Wanli, Grzegorzek Marcin

Biocybernetics and Biomedical Engineering

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2022

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Vol. 42, no. 1

204--214

EN

Computer-Aided Sperm Analysis (CASA) is a widely studied topic in the diagnosis and treatment of male reproductive health. Although CASA has been evolving, there is still a lack of publicly available large-scale image datasets for CASA. To fill this gap, we provide the Sperm Videos and Images Analysis (SVIA) dataset, including three different subsets, subset-A, subset-B and subset-C, to test and evaluate different computer vision techniques in CASA. For subset-A, in order to test and evaluate the effectiveness of SVIA dataset for object detection, we use five representative object detection models and four commonly used evaluation metrics. For subset-B, in order to test and evaluate the effectiveness of SVIA dataset for image segmentation, we used eight representative methods and three standard evaluation metrics. Moreover, to test and evaluate the effectiveness of SVIA dataset for object tracking, we have employed the traditional kNN with progressive sperm (PR) as an evaluation metric and two deep learning models with three standard evaluation metrics. For subset-C, to prove the effectiveness of SVIA dataset for image denoising, nine denoising filters are used to denoise thirteen kinds of noise, and the mean structural similarity is calculated for evaluation. At the same time, to test and evaluate the effectiveness of SVIA dataset for image classification, we evaluate the results of twelve convolutional neural network models and six visual transformer models using four commonly used evaluation metrics. Through a series of experimental analyses and comparisons in this paper, it can be concluded that this proposed dataset can evaluate not only the functions of object detection, image segmentation, object tracking, image denoising, and image classification but also the robustness of object detection and image classification models. Therefore, SVIA dataset can fill the gap of the lack of large-scale public datasets in CASA and promote the development of CASA. Dataset is available at: .https://github.com/Demozsj/Detection-Sperm.

2

Dataset enhancement in hair follicle detection: ESENSEI challenge

Jakubik J.

Annals of Computer Science and Information Systems

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2018

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Vol. 16

19--22

EN

In this paper, a solution to ESENSEI data mining challenge concerning the analysis of microscopic hair images is described. The task of the challenge was to detect locations of hair follicles in closeup images of a human scalp. The proposed solution is based on a convolutional neural network architecture. To improve generalization performance, we enhance training and test datasets using image transformations applied to both input and output. The chosen transformations are two axis symmetries and switching axes, all of which are possible to apply regardless of resolution without producing interpolation artifacts. Since these can be combined, 2^3 = 8 possible views of each image can be created to expand both training and test data. We demonstrate the effects of dataset enhancement in both training and classifying on results achievable on the competition dataset. The solution placed 2nd in the final challenge evaluation.

3

A novel approach for detection and delineation of cell nuclei using feature similarity index measure

John J., Nair M. S., Kumar P. R. A., Wilscy M.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 1

76--88

EN

Accurate image segmentation of cells and tissues is a challenging research area due to its vast applications in medical diagnosis. Seed detection is the basic and most essential step for the automated segmentation of microscopic images. This paper presents a robust, accurate and novel method for detecting cell nuclei which can be efficiently used for cell segmentation. We propose a template matching method using a feature similarity index measure (FSIM) for detecting nuclei positions in the image which can be further used as seeds for segmentation tasks. Initially, a Fuzzy C-Means clustering algorithm is applied on the image for separating the foreground region containing the individual and clustered nuclei regions. FSIM based template matching approach is then used for nuclei detection. FSIM makes use of low level texture features for comparisons and hence gives good results. The performance of the proposed method is evaluated on the gold standard dataset containing 36 images (_8000 nuclei) of tissue samples and also in vitro cultured cell images of Stromal Fibroblasts (5 images) and Human Macrophage cell line (4 images) using the statistical measures of Precision and Recall. The results are analyzed and compared with other state-of-the-art methods in the literature and software tools to prove its efficiency. Precision is found to be comparable and the Recall rate is found to exceed 92% for the gold standard dataset which shows considerable performance improvement over existing methods.

4

Estimation of copper concentrate grade based on color features and least-squares support vector regression

Ren C., Yang J., Liang C.

Physicochemical Problems of Mineral Processing

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2015

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Vol. 51, iss. 1

163--172

EN

In this paper, a new method based on color features of microscopic image and least-squares support vector regression model (LS-SVR) is proposed for indirect measurement of copper concentrate grade. Red, green and blue (RGB), hue and color vector angle were extracted from color microscopic images of a copper concentrate sample and selected for the comparison. Three different estimation models based on LS-SVR were developed using RGB, hue, and color vector angle, respectively. A comparison of three models was carried out through a validation test. The best model was obtained for the hue giving a running time of 30.243 ms, root mean square error of 0.8644 and correlation coefficient value of 0.9997. The results indicated that the copper concentrate grade could be estimated by the LS-SVR model using the hue as input parameter with a satisfactory accuracy.

5

New image processing algorithms in computer vision systems for phatomorphologic diagnostic

Bieniecki W.

Zeszyty Naukowe. Elektryka / Politechnika Łódzka

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2006

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z. 109

5-14

EN

In this paper main contributions of the author`s Ph. D. dissertation are summarized. The aim of the research was to develop two image processing systems for biomedicine: a system of automatic breast cancer nuclei classification and a system for immunoenzymatic lymphocyte response measurement. Standard image processing algorithms are insufficient for the completion of the task, so new algorithms had to be proposed. These include noise removal from color images, enhanced binarization method, pixel classification algorithm and watershed-based segmentation algorithm.

PL

W artykule zaprezentowano najważniejsze osiągnięcia autora pracy doktorskiej. Celem pracy było zaprojektowanie dwóch systemów automatycznego przetwarzania obrazów dla potrzeb biomedycyny: system rozpoznawania komórek tkanki raka piersi i system badania komórek układu odpornościowego po przeszczepie nerki. Istniejące algorytmy przetwarzania obrazu okazały się niewystarczające do realizacji zadania. Autor pracy zaproponował zmodyfikowane algorytmy: usuwanie szumu impulsowego z obrazów barwnych, wieloprzebiegowy algorytm binaryzacji obrazu, metoda klasyfikacji pikseli i algorytm segmentacji oparty o metodę działów wodnych.

6

Porównanie rodzajów sterylizacji na podstawie wyników badań mikroskopowych sterylizowanych włókien światłowodowych

Stawarz M., Podbielska H.

Acta Bio-Optica et Informatica Medica. Inżynieria Biomedyczna

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2001

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Vol. 7, nr 3-4

123-131

PL

W niniejszej pracy przedstawiono wyniki badań nad wpływem sterylizacji na parametry optyczne włókien światłowodowych. Sterylizację wykonano dwiema technikami: niskotemperaturową (plazmową) i wysokotemperaturową (parową). Badano transmisję światła przez światłowody prostopadle do długiej osi. Transmisję oceniano na podstawie obrazu mikroskopowego odcinków światłowodów, wyznaczając histogramy i luminancje obrazów. Udowodniono, że sterylizacja plazmowa jest mniej niszcząca dla światłowodów niż sterylizacja parowa.

EN

The results of investigation of sterilization influence on optical parameters of fibers are discussed in this work. Two methods of sterilization were applied: low temperature process (plasma sterilization) and high temperature one (by means of hot steam). The light transmission was examined perpendicular to the fiber long axis. The transmission was evaluated basing on the microscopic image of the fiber by calculating the image histogram and luminance. It was stated that plasma sterilization is less damaging to the fiber than this one by hot steam.

7

Zaawansowane zagadnienia komputerowego przetwarzania i analizy obrazu mikroskopowego

Wojnar L.

LAB Laboratoria, Aparatura, Badania

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2000

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R. 5, nr 4

34-40

8

Komputerowe przetwarzanie i analiza obrazu mikroskopowego

Wojnar L.

LAB Laboratoria, Aparatura, Badania

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2000

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R. 5, nr 3

14-19

9

Computerised system for detecting cell forms in the urine combined with the microscope analysis

Dyszkiewicz A., Koprowski R., Wróbel Z.

Journal of Medical Informatics & Technologies

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2000

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Vol. 1

BI 59--65

EN

The study presents the computerised system of urogical monitoring of patients with catheters in their bladders. The phenomenon of capacity resistance which is caused by live cells in solutions under the influence of the low frequency alternating current was used to build a sensor. The sensor indicates the presence of live cells and red or white blood cells in the urine, when the need of an immedicate treatment is obvious. The measuring part of the sensor consists of an induction loop which is adjusted to the measuring of the urine resistance by means of alternating current and the pair of electrodes to measure the resistance by direct current and a digital system for comparing the values of the resistance for alternating and direct current. When any cells forms are present, during the measuring by alternating current capacity resistance is added to the ohm resistance. If the cell forms are present, the capacity resistance does not appear. The mathematical proportion between the resistance values for direct and alternating current is proportional to the amount of cells in the solution. In the calibration process, indications of the ohmometer are compared to the digital microscopic image of the given urine sample. A direct relation between the resistance factor value and the cell concentration in urine is then obtained.

PL

W opracowaniu przedstawiony został skomputeryzowany system nadzoru urologicznego nad pacjentem z wprowadzonym do pęcherza moczowego cewnikiem. Wykorzystując zjawisko reaktancji pojemnościowej generowanej przez żywe komórki w roztworach pod wpływem prądu zmiennego m.cz zbudowany został czujnik reagujący na pojawianie się moczu żywych bakterii, krwinek białych i czerwonych, sygnalizujących potrzebę włączenia natychmiastowego leczenia. Część pomiarowa czujnika zbudowana jest z pary elektrod do pomiaru oporności napięciem stałym lub zmiennym małej częstotliwości oraz układu cyfrowego dokonującego porównania modułu impedancji. W przypadku pojawienia się elementów komórkowych, podczas pomiaru napięciem zmiennym do oporności wyznaczonej dla napięcia stałego dołącza się reaktancja pojemnościowa, natomiast jeżeli elementy morfotyczne nie występują reaktancja pojemnościowa się nie pojawia. Matematyczna proporcja pomiędzy wartością modułu impedancji dla napięcia stałego lub zmiennego m.cz w stosunku do w.cz, jest proporcjonalna do ilości komórek w roztworze. W procesie kalibracji wartość modułu impedancji jest konfrontowana z cyfrowym obrazem mikroskopowym danej próbki moczu, w której dokonujemy obliczeń ilości bakterii lub komórek przypadających na milimetr kwadratowy powierzchni. Uzyskujemy wówczas bezpośrednią zależność wartości współczynnika impedancji od koncentracji komórek w badanym moczu.