Technology of intellectual feature selection for a system of automatic formation of a coagulate plan on retina

Ilyasova, Nataly; Shirokanev, A. S.; Kupriyanov, Alexander; Paringer, Rustam

doi:10.18287/2412-6179-2019-43-2-304-315

Cited by 28 publications

(5 citation statements)

References 23 publications

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“…Therefore, we displaced the image in Figure 4, rotated it by certain angles, and scaled it. The values of displacement, angles, and scaling coefficient were determined using reference points [22][23][24][25][26]. The reference points on the image (see Figure 3 We investigated the dynamics of graft biotransformation using the proposed method.…”

Section: Methodsmentioning

confidence: 99%

Technology for High-Sensitivity Analysis of Medical Diagnostic Images

Абульханов¹,

Slesarev²,

Strelkov³

et al. 2021

Sovrem Tehnol Med

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Control and analysis of small, inaccessible to human vision changes in medical images make it possible to focus on diagnostically important radiological signs important for the correct diagnosis.The aim of the study was to develop information technology facilitating the early diagnosis of diseases using medical images. Materials and Methods. To control changes in the image, we used its transformation based on solving a particular case of the knapsack problem. The proposed transformation is highly sensitive to any changes in the image and provides the possibility to record deviations visually with high accuracy. Medical images were obtained using cone beam computed tomography.Results. Practical evaluation of the information technology on tomograms showed the following: the transformed images of healthy bone tissue fragments from different parts of the jaw have similar shapes and nearly the same range of brightness. The transformed image of bone tissue after treatment has a shape close to that of the transformed image of healthy bone tissue. The transformed image of the affected bone tissue has a shape and brightness range differing from the shape and color of the transformed images of healthy bone tissue and bone tissue after treatment. However, transformation of medical images obtained with the Planmeca ProMax 3D Classic device (Finland) allows recording changes that account for less than 0.0001% of the entire image.Conclusion. The proposed method allows human vision to capture changes as small as nearly one pixel in the transformed image, which is impossible with the original medical image. Increasing the color contrast of the transformed medical image makes it possible to reveal the structure of the analyzed medical image fragment. The proposed image transformation method can be used for early diagnosis of diseases and in other fields of medicine.

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Section: Methodsmentioning

confidence: 99%

Technology for High-Sensitivity Analysis of Medical Diagnostic Images

Абульханов¹,

Slesarev²,

Strelkov³

et al. 2021

Sovrem Tehnol Med

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“…The deviation map is built by evaluating the difference between the OCT-aided retinal thick-ness map and that of a healthy retina. As a result, a map of the regions to be photo-coagulated is created [27,28].…”

Section: Technology Of Mapping a Laser Photocoagulation Planmentioning

confidence: 99%

“…2). The technology is aimed at mapping an effective photocoagulation pattern [27]. The ophthalmologist will be able to correct the processing result for any block in the diagram in fig.…”

Section: Technology Of Mapping a Laser Photocoagulation Planmentioning

confidence: 99%

Decision-making support system for the personalization of retinal laser treatment in diabetic retinopathy

Ilyasova¹,

Kirsh²,

Demin³

2022

Computer Optics

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In this work, we propose a decision-making support system for automatically mapping an effective photocoagulation pattern for the laser treatment of diabetic retinopathy. The purpose of research to create automated personalization of diabetic macular edema laser treatment. The results are based on analysis of large semi-structured data, methods and algorithms for fundus image processing. The technology improves the quality of retina laser coagulation in the treatment of diabetic macular edema, which is one of the main reasons for pronounced vision decrease. The proposed technology includes original solutions to establish an optimal localization of multitude burns by determining zones exposed to laser. It also includes the recognition of large amount of unstructured data on the anatomical and pathological locations' structures in the area of edema and data optical coherent tomography. As a result, a uniform laser application on the pigment epithelium of the affected retina is ensured. It will increase the treatment safety and its effectiveness, thus avoiding the use of more expensive treatment methods. Assessment of retinal lesions volume and quality will allow predicting the laser photocoagulation results and will contribute to the improvement of laser surgeon's skills. The architecture of a software complex comprises a number of modules, including image processing methods, algorithms for photocoagulation pattern mapping, and intelligent analysis methods.

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“…To study the selected features, an intelligent analysis technology was developed, allowing the quality of classification to be analyzed using the method of discriminant analysis (Figure 5) [38]. The first stage is to categorize the database of operations performed, described by the image of the fundus and the set of arranged coagulates, into the classes "successful operation" and "unsuccessful operation" according to the scoring system described in Section 2.2.…”

Section: Technology For Intelligent Analysis Of the Photocoagulation ...mentioning

confidence: 99%

Identification of Prognostic Factors and Predicting the Therapeutic Effect of Laser Photocoagulation for DME Treatment

et al. 2021

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Diabetic retinopathy is among the most severe complications of diabetes, most often leading to rapid and irreversible vision loss. The laser coagulation procedure, which consists of applying microburns to the fundus, has proven to be an effective method for treating diabetic retinopathy. Unfortunately, modern research does not pay enough attention to the study of the arrangement of microburns in the edema area—one of the key factors affecting the quality of therapy. The aim of this study was to propose a computational decision-making support system for retina laser photocoagulation based on the analysis of photocoagulation plans. Firstly, we investigated a set of prognostic factors based on 29 features describing the geometric arrangement of coagulates. Secondly, we designed a technology for the intelligent analysis of the photocoagulation plan that allows the effectiveness of the treatment to be predicted. The studies were carried out using a large database of fundus images from 108 patients collected in clinical trials. The results demonstrated a high classification accuracy at a level of over 85% using the proposed prognostic factors. Moreover, the designed technology proved the superiority of the proposed algorithms for the automatic arrangement of coagulates, predicting a 99% chance of a positive therapeutic effect.

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Technology of intellectual feature selection for a system of automatic formation of a coagulate plan on retina

Cited by 28 publications

References 23 publications

Technology for High-Sensitivity Analysis of Medical Diagnostic Images

Technology for High-Sensitivity Analysis of Medical Diagnostic Images

Decision-making support system for the personalization of retinal laser treatment in diabetic retinopathy

Identification of Prognostic Factors and Predicting the Therapeutic Effect of Laser Photocoagulation for DME Treatment

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