Wyniki wyszukiwania - Biblioteka Nauki

1

A Neural Network Model for Object Mask Detection in Medical Images

100%

Tereikovskyi I. , Korchenko O. , Bushuyev S. , Tereikovskyi O. , Ziubina R. , Veselska O.

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2023

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tom Vol. 69, No. 1

41--46

EN

In modern conditions in the field of medicine, raster image analysis systems are becoming more widespread, which allow automating the process of establishing a diagnosis based on the results of instrumental monitoring of a patient. One of the most important stages of such an analysis is the detection of the mask of the object to be recognized on the image. It is shown that under the conditions of a multivariate and multifactorial task of analyzing medical images, the most promising are neural network tools for extracting masks. It has also been determined that the known detection tools are highly specialized and not sufficiently adapted to the variability of the conditions of use, which necessitates the construction of an effective neural network model adapted to the definition of a mask on medical images. An approach is proposed to determine the most effective type of neural network model, which provides for expert evaluation of the effectiveness of acceptable types of models and conducting computer experiments to make a final decision. It is shown that to evaluate the effectiveness of a neural network model, it is possible to use the Intersection over Union and Dice Loss metrics. The proposed solutions were verified by isolating the brachial plexus of nerve fibers on grayscale images presented in the public Ultrasound Nerve Segmentation database. The expediency of using neural network models U-Net, YOLOv4 and PSPNet was determined by expert evaluation, and with the help of computer experiments, it was proved that U-Net is the most effective in terms of Intersection over Union and Dice Loss, which provides a detection accuracy of about 0.89. Also, the analysis of the results of the experiments showed the need to improve the mathematical apparatus, which is used to calculate the mask detection indicators.

2

The universal quality index for medical images

88%

Lisowska A. , Kotarski W.

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tom Vol. 3

MI199--206

EN

The aim of this paper is to propose a new quality index which measures the distance between a reference (source) image and its corrupted copy in the way as Human Visual System (HVS) does. The new quality index called the Mean Weighted Quality Index (MW) is defined with the help of the well known easy calculated indexes. The experiments performed on a number of medical images confirmed usefulness of the new index.

3

An introduction to watermarking of medical images

88%

Wójtowicz W.

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tom Vol. 9, no. 1

9--16

EN

This paper provides a preliminary investigation on digital watermarking as an effective technology to protect property rights and limit distribution of multimedia data. First, crucial properties and design requirements of watermarking schemes are discussed. Then, as watermarking techniques finds many applications in healthcare industry, aspects of medical image watermarking are raised. Nowadays, the transmission of digitized medical information has become very easy due to the generality of Internet. However, the digital form of these images can easily be manipulated and degraded. This causes problems of medical security and copyright protection and poses a great challenge to privacy protection using watermarking techniques.

4

The half-byte descriptor for image data units

75%

Czapla Z.

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2007

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tom Vol. 11

115--121

EN

The paper presents proposal for image data unit description using a half-byte format. It was implemented for medical images description. The introduced definitions express pixel values using differences between pixels and the introduced base value. This way the image recorded at half-byte format can be simply compressed by an appropriate compression, methods more effectively. The half-byte format is suitable for so called "natural" images with textures that are usually compressed with not satisfying results. For the given method illustration some example results were introduced.

5

A transputer implementation of systolic arrays design for low-level medical image processing

63%

Amin S. , Saeed M.

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tom Vol. 6, no 3-4

35-45

EN

Many low-level image processing operations, termed local operators, require access to the four or eight neighbouring intensity values of a pixel, when computing the new value for the pixel and need large amounts of computing i.e., banded matrix operations. However, these algorithms contain explicit parallelism which can be efficiently exploited by processor arrays. The purpose of this paper is to identify a set of systolic array designs suitable for implementing low level image processing algorithms for medical images of tissues on VLSI processing arrays, in particular we consider the sigma, inverse gradient and mean filters. To achieve high performance we have developed several models of systolic arrays. One of the aims of this is to design and build a programming workbench for developing image processing operations for low-level vision. The motivation for the work is to develop a methodology for the implementation of an image processing library on the Transputer network, which holds a library of precoded software components in a generalised configuration-independent style for medical images. The digital image processing filter library is discussed in thispaper.