Classification Method for Macular Lesions Using Fuzzy Thresholding Method

Kubíček, Jan; Penhaker, Marek; Bryjova, Iveta; Augustýnek, Martin

doi:10.1007/978-3-319-32703-7_48

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…al. [11] has shown the use of Fuzzy Segmentation in classifying the macular lesions in OCT images. Several other machine learning algorithms have also been used where a number of techniques were utilized in classification of the AMD grades and stages [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Smart AMD prognosis through cellphone: an innovative localized AI-based prediction system for anti-VEGF treatment prognosis in nonagenarians and centenarians

Qidwai

Raja

et al. 2022

Int Ophthalmol

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Background and ObjectiveAge-related macular-degeneration (AMD) is one of the most common reasons for blindness in the world today. The most common treatment for wet AMD is the intra-vitreal injections for inhibiting Vascular-Endothelial-Derived-Growth-Factor (VEGF). This treatment usually involves multiple injections and thus multiple clinic visits which not only causes increased cost on national health services but also causes exposure to the hospital environment which is sometimes high risk considering current COVID crisis. The treatment, in spite of the above concerns, is usually effective. However, in some cases, either the medicine fails to produce the anticipated favorable outcome, resulting in waste of time, medication, efforts, and above all, psychological distress to the patients. Hence, early predictability of anatomical as well as functional effectiveness of the treatment appears to be a very desirable capability to have. MethodA Machine Learning approach using Adaptive Neuro-Fuzzy Inference System (ANFIS) twosample prediction model has been presented that requires only the base line measurements and changes in Visual Acuity (VA) as well as Macular Thickness (MAC) after four months of treatment to estimate the values of VA and MAC at 8 th and 12 th months. In contrast to most of the AI techniques, ANFIS approach has shown the capability of the algorithm to work with very small dataset as well, which makes it a perfect candidate for the presented solution. ResultsThe presented model has shown to have a very high accuracy (>92%) and works in near-realtime scenarios. It has been converted into a smart-phone-App, Ophnosis AMD , for convenient usage. With this App, the clinician can visualize the progression of the patient for a specific treatment and can decide on continuing or changing the treatment accordingly. The complete AIengine developed with ANFIS algorithm is localized to the phone through the App, implying that there is no need for internet or cloud connectivity for this App to function. This makes it ideal for remote usage, especially under the current COVID scenarios. ConclusionsWith a smart AI-based App on their fingertips, the presented system provides ample opportunity to the doctors to make a better decision based on the estimated progression, if the same drug is continued with (Good/Fair Prognosis) or alternate treatment should be sought (Bad Prognosis). From a functional point of view, a prediction algorithm is triggered through simple entry of the relevant parameters (base-line and 4 months only). No internet/cloud connectivity is needed since the algorithm and the trained network are fully embedded in the App locally. Hence, using the App in remote and/or non-connected isolated areas is possible, especially in the secluded patients during the COVID scenarios.

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Section: Introductionmentioning

confidence: 99%

Smart AMD prognosis through cellphone: an innovative localized AI-based prediction system for anti-VEGF treatment prognosis in nonagenarians and centenarians

Qidwai

Raja

et al. 2022

Int Ophthalmol

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“…We use optimized Otsu method utilizing of multi-thresholding increasing sensitivity of blood vessel segmentation and extraction of vascular calcifications [1,17,18]. The core of the method is finding a specific intensity level on a base of the histogram distribution into evenly large areas.…”

Section: Multilevel Thresholding Algorithm For Vascular Calcificationsmentioning

confidence: 99%

Modeling and objectification of blood vessel calcification with using of multiregional segmentation

Kubíček

Bryjova

Valošek

et al. 2018

Vietnam J Comput Sci

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In a clinical practice of the angiography, the blood vessel analysis is substantially important mainly in a sense of an objectification and modeling of the pathological spots such as the blood vessel calcifications. An amount of the calcification is commonly just estimated by naked eyes; therefore, the automatic modeling may be beneficial in a context of an extraction of the blood vessel features well representing a level of the blood vessel deterioration. In this work, we have proposed a fully automatic software environment (BloodVessCalc) for processing the blood vessel images acquired by the CT (computer tomography). The main function of the SW is the multiregional image segmentation allowing for an extraction of the physiological blood vessel location from the calcification spots. This model offers the calcium score calculation in a form of amount of the calcification. In the last part of our analysis, the predictive intervals of the average value and median for calcium score are calculated.

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Extraction of Optical Disc Geometrical Parameters with Using of Active Snake Model with Gradient Directional Information

Kubíček

Timkovič

Penhaker

et al. 2017

Intelligent Information and Database Systems

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Classification Method for Macular Lesions Using Fuzzy Thresholding Method

Cited by 7 publications

References 9 publications

Smart AMD prognosis through cellphone: an innovative localized AI-based prediction system for anti-VEGF treatment prognosis in nonagenarians and centenarians

Smart AMD prognosis through cellphone: an innovative localized AI-based prediction system for anti-VEGF treatment prognosis in nonagenarians and centenarians

Modeling and objectification of blood vessel calcification with using of multiregional segmentation

Extraction of Optical Disc Geometrical Parameters with Using of Active Snake Model with Gradient Directional Information

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