Yes / Purpose To record transient ERGs from the lightadapted human retina using silent substitution stimuli which selectively reflect the activity of rod photoreceptors. We aim to describe the morphology of these waveforms and examine how they are affected by the use of less selective stimuli and by retinal pathology. Methods Rod-isolating stimuli with square-wave temporal profiles (250/250 ms onset/offset) were presented using a 4 primary LED ganzfeld stimulator. Experiment 1: ERGs were recorded using a rodisolating stimulus (63 ph Td, rod contrast, Crod = 0.25) from a group (n = 20) of normal trichromatic observers. Experiment 2: Rod ERGs were recorded from a group (n = 5) using a rodisolating stimulus (Crod = 0.25) which varied in retinal illuminance from 40 to 10,000 ph Td. Experiment 3: ERGs were elicited using 2 kinds of nonisolating stimuli; (1) broadband and (2) rod-isolating stimuli which contained varying degrees of L- and M-cone excitation. Experiment 4: Rod ERGs were recorded from two patient groups with rod monochromacy (n = 3) and CSNB (type 1; n = 2). Results The rod-isolated ERGs elicited from normal subjects had a waveform with a positive onset component followed by a negative offset. Response amplitude was maximal at retinal illuminances\100 ph Td and was virtually abolished at 400 ph Td. The use of non-selective stimuli altered the ERG waveform eliciting more photopic-like ERG responses. Rod ERGs recorded from rod monochromats had similar features to those recorded from normal trichromats, in contrast to those recorded from participants with CSNB which had an electronegative appearance. Conclusions Our results demonstrate that ERGs elicited by silent substitution stimuli can selectively reflect the operation of rod photoreceptors in the normal, light-adapted human retina. / Deutsche Forschungsgemeinschaft (DFG) (KR1317/13-1) and Bundesministerium für Bildung und Forschung (BMBF) (01DN14009) provided financial support for JK.

Yes / We studied the spatial arrangement of L- and M-cone driven electroretinograms (ERGs) reflecting the activity of magno- and parvocellular pathways. L- and M-cone isolating sine wave stimuli were created with a four primary LED stimulator using triple silent substitution paradigms. Temporal frequencies were 8 and 12 Hz, to reflect cone opponent activity, and 30, 36 and 48 Hz to reflect luminance activity. The responses were measured for full-field stimuli and for different circular and annular stimuli. The ERG data confirm the presence of two different mechanisms at intermediate and high temporal frequencies. The responses measured at high temporal frequencies strongly depended upon spatial stimulus configuration. In the full-field conditions, the L-cone driven responses were substantially larger than the full-field M-cone driven responses and also than the L-cone driven responses with smaller stimuli. The M-cone driven responses at full-field and with 70° diameter stimuli displayed similar amplitudes. The L- and M-cone driven responses measured at 8 and 12 Hz were of similar amplitude and approximately in counter-phase. The amplitudes were constant for most stimulus configurations. The results indicate that, when the ERG reflects luminance activity, it is positively correlated with stimulus size. Beyond 35° retinal eccentricity, the retina mainly contains L-cones. Small stimuli are sufficient to obtain maximal ERGs at low temporal frequencies where the ERGs are also sensitive to cone-opponent processing

Yes / Purpose: To demonstrate that silent substitution stimuli can be used to generate electroretinograms (ERGs) that effectively isolate rod photoreceptor function in humans without the need for dark adaptation, and that this approach constitutes a viable alternative to current clinical standard testing protocols. Methods: Rod-isolating and non-isolating sinusoidal flicker stimuli were generated on a 4 primary light-emitting diode (LED) Ganzfeld stimulator to elicit ERGs from participants with normal and compromised rod function who had not undergone dark-adaptation. Responses were subjected to Fourier analysis, and the amplitude and phase of the fundamental were used to examine temporal frequency and retinal illuminance response characteristics. Results: Electroretinograms elicited by rod-isolating silent substitution stimuli exhibit low-pass temporal frequency response characteristics with an upper response limit of 30 Hz. Responses are optimal between 5 and 8 Hz and between 10 and 100 photopic trolands (Td). There is a significant correlation between the response amplitudes obtained with the silent substitution method and current standard clinical protocols. Analysis of signal-to-noise ratios reveals significant differences between subjects with normal and compromised rod function. Conclusions: Silent substitution provides an effective method for the isolation of human rod photoreceptor function in subjects with normal as well as compromised rod function when stimuli are used within appropriate parameter ranges. Translational Relevance: This method of generating rod-mediated ERGs can be achieved without time-consuming periods of dark adaptation, provides improved isolation of rod- from cone-based activity, and will lead to the development of faster clinical electrophysiologic testing protocols with improved selectivity.

The work in this thesis is concerned with examining the retinal and cortical contributions to human trichromatic colour vision. Chromatic processing at the cortex level was examined using visual evoked potentials (VEPs). These responses were elicited by chromatic spot stimuli, which were manipulated in order to selectively activate the chromatic processing system. Chromatic processing at the retinal level was examined using the electroretinograms (ERGs) for which cone isolating stimuli were used to assess the nature of L and M cone inputs to cone-opponent mechanisms. The results from the VEP experiments suggest VEP morphology is dependent upon 1) chromatic and or luminance contrast content of the stimulus, 2) stimulus size, and 3) extent to which the chromatic stimulus activates either the L/M or S/(L+M) opponent mechanism. The experiments indicate that chromatic stimulation is indexed by large N1 component and small offset responses. Optimal stimulus size for chromatic isolation is 2-4 ° along L/M axes and 6° along S/(L+M) axis. From the ERG experiments, It has been shown that the low (12Hz) and high (30Hz) temporal frequency flickering stimuli can isolate the chromatic and luminance processing mechanisms in the retina. For low temporal frequency ERGs, the L:M ratio was close to unity and L/M phase difference was close to 180°. For high temporal frequency ERGs, the L:M ratio was more than unity and L/M phase difference was close to 90°. In addition to this, the variation in L:M ratio across the retinal eccentricity was also examined. These results suggest, for the chromatic processing, L:M ratio is close to unity independent of retinal eccentricity and individuals. For the luminance processing, L:M ratio is more than unity and depends upon the region of the retina being stimulated. These findings indicate the maintenance of cone selective input for the chromatic processing across the human retina.

The work in this thesis is concerned with examining the retinal and cortical contributions to human trichromatic colour vision. Chromatic processing at the cortex level was examined using visual evoked potentials (VEPs). These responses were elicited by chromatic spot stimuli, which were manipulated in order to selectively activate the chromatic processing system. Chromatic processing at the retinal level was examined using the electroretinograms (ERGs) for which cone isolating stimuli were used to assess the nature of L and M cone inputs to cone-opponent mechanisms. The results from the VEP experiments suggest VEP morphology is dependent upon 1) chromatic and or luminance contrast content of the stimulus, 2) stimulus size, and 3) extent to which the chromatic stimulus activates either the L/M or S/(L+M) opponent mechanism. The experiments indicate that chromatic stimulation is indexed by large N1 component and small offset responses. Optimal stimulus size for chromatic isolation is 2-4 ° along L/M axes and 6° along S/(L+M) axis. From the ERG experiments, It has been shown that the low (12Hz) and high (30Hz) temporal frequency flickering stimuli can isolate the chromatic and luminance processing mechanisms in the retina. For low temporal frequency ERGs, the L:M ratio was close to unity and L/M phase difference was close to 180°. For high temporal frequency ERGs, the L:M ratio was more than unity and L/M phase difference was close to 90°. In addition to this, the variation in L:M ratio across the retinal eccentricity was also examined. These results suggest, for the chromatic processing, L:M ratio is close to unity independent of retinal eccentricity and individuals. For the luminance processing, L:M ratio is more than unity and depends upon the region of the retina being stimulated. These findings indicate the maintenance of cone selective input for the chromatic processing across the human retina.

No / Cone isolating stimuli were used to assess the temporal frequency response characteristics of L- and M-cone electroretinograms (ERGs) in nine trichromatic and four dichromatic human observers. The stimuli comprised sinusoidal temporal modulations varying from 5 to 100 Hz. ERGs were recorded using corneal fiber electrodes and subjected to fast Fourier transform analysis. At low temporal frequencies (<10  Hz<10  Hz) the L- and M-cone ERGs had similar amplitude and exhibited minimal differences in apparent latency. At higher flicker rates (>20  Hz>20  Hz) L-cone ERGs had greater amplitudes and shorter apparent latencies than the M-cone responses. These differences between the L- and M-cone ERGs are consistent with their mediation by chromatic and luminance postreceptoral processing pathways at low and high temporal frequencies, respectively.

No / Electroretinograms (ERGs) elicited by transient, square-wave L- and M-cone isolating stimuli were recorded from human trichromatic (n=19) and dichromatic (n=4) observers. The stimuli were generated on a 4 primary LED stimulator and were equated in terms of cone modulation (cone contrast = 0.11) and retinal illuminance (12,000 trolands). L- and M-cone isolated ERGs had waveforms similar to those observed for luminance responses. However, M-cone ERGs exhibited a phase reversal in their responses to onset and offset stimuli relative to the L-cone responses. This on-off response reversal was observed in trichromats but not dichromats. Simultaneous counter-phase and in-phase combinations of L- and M-cone isolating stimuli generated responses that reflected chromatic and luminance processing, respectively. We conclude that L- and M-cone specific ERGs provide a measure of how photoreceptors contribute to post-receptoral mechanisms.

В последние годы распространенность сердечно-сосудистых заболеваний, а также уровень смертности растет, что серьезно угрожает здоровью человека, что требует от врачей ранней диагностики сердечно-сосудистых заболеваний, чтобы выиграть время для последующего лечения пациентов, а результаты сегментации ультразвуковых изображений левого желудочка могут помочь врачам в диагностике сердечно-сосудистых заболеваний, но ультразвуковые изображения левого желудочка имеют характеристики сильного шума, слабых границ и сложной структуры ткани, что делает сегментацию изображения сложной, низкой эффективностью и плохой точностью. Одним из важнейших этапов оценки здоровья сердца является отслеживание и сегментация эндокардиальной границы левого желудочка (ЛЖ) с помощью ЭхоКГ, которая используется для измерения фракции выброса и оценки движения региональной стенки. Недостатком этих методов является необходимость применения обработки изображений вручную или в полуавтоматическом режиме, что требует специальных знаний и навыков. В результате вопрос автоматического отслеживания и сегментации ЛЖ на ЭхоКГ-изображениях является актуальной и практической проблемой. В моем проекте изучается способность полностью обученных моделей глубокого обучения U-Net, U-Net++, MANet, LinkNet, FPN, PSPNet, PAN, DeepLabv3 и DeepLabv3+ автоматически определять область левого желудочка. В то же время в архитектурах U-Net, U-Net++, MANet, LinkNet, PSPNet, PAN, FPN, DeepLabv3 и DeepLabv3+ модули кодировщика затем последовательно заменялись на ResNet18, ResNet34, ResNet5, ResNet101, EfficientNet-b0, EfficientNet-b1, EfficientNet-b3, EfficientNet-b5, EfficientNet-b7 и MobileNetv2, а ImageNet использовался в качестве весов предварительной подготовки; Добавление магистральных сетей в архитектуру модели приводит к более высокой точности сегментации по сравнению с исходной моделью. В рамках той же архитектуры модели EfficientNet в качестве кодировщика достигает лучших результатов сегментации, а EfficientNet-b3 работает лучше. Аналогично, в рамках серии ResNet ResNet34 работает лучше. В модели сегментации этого эксперимента Deeplabv3+ показывает превосходную производительность. Это указывает на то, что в архитектуре модели этого эксперимента интеграция модулей ResNet34 и EfficientNet-b3 в качестве кодировщиков может эффективно и осуществимо автоматизировать распознавание эндокардиальной границы левого желудочка на ультразвуковых изображениях. Кроме того, аугментация данных также в определенной степени повысит точность сегментации модели. / In recent years, the prevalence of cardiovascular diseases. as well as the mortality rate is increasing, which has seriously threatened human health, which requires doctors to diagnose cardiovascular diseases early to gain time for patients' later treatment, and the segmentation results of left ventricular ultrasound images can assist doctors in the diagnosis of cardiovascular diseases, but the left ventricular ultrasound images have the characteristics of strong noise, weak edges and complex tissue structure, which makes the image segmentation difficult, low efficiency and poor precision. One of the most important steps in estimating the health of the heart is the tracking and segmentation of the left ventricular (LV) endocardial border from EchoCG, which is used for measuring the ejection fraction and assessing the regional wall motion. The disadvantage of these methods is the necessity to apply image processing manually or in a semi-automatic mode, which requires special knowledge and skills. As a result, the issue of an automatic tracking and segmentation of the LV on EchoCG-images is an actual and practical problem. In my project, the ability of fully trained Deep Learning Models U-Net, U-Net++, MANet, LinkNet, FPN, PSPNet, PAN, DeepLabv3and DeepLabv3+ to automatically identify the left ventricular region is explored. At the same time, in the U-Net, U-Net++, MANet, LinkNet, PSPNet, PAN, FPN, DeepLabv3 and DeepLabv3+ architectures, the encoder modules were then sequentially replaced with ResNet18, ResNet34, ResNet5, ResNet101, EfficientNet-b0, EfficientNet-b1, EfficientNet-b3, EfficientNet-b5, EfficientNet-b7and MobileNetv2, and ImageNet was used as the pre-training weights; The addition of backbones to the model architecture leads to higher segmentation accuracy compared to the original model. Within the same model architecture, EfficientNet as the encoder achieves better segmentation results, with EfficientNet-b3 performing the best. Similarly, within the ResNet series, ResNet34 performs better. In the segmentation model of this experiment, Deeplabv3+ shows superior performance. This indicates that in the model architecture of this experiment, integrating ResNet34 and EfficientNet-b3 modules as encoders can effectively and feasibly automate the recognition of the endocardial boundary of the left ventricle in ultrasound images. Furthermore, data augmentation will also enhance the model’s segmentation accuracy to a certain extent.

Электроретинография (ЭРГ) — это неинвазивный способ измерения электрической активности сетчатки с помощью световой стимуляции. Сигналы ЭРГ содержат несколько различных компонентов, которые можно использовать для диагностики различных заболеваний сетчатки. Некоторые из этих заболеваний включают дистрофии, связанные с колбочками и палочками, возрастную дегенерацию желтого пятна, диабетическую ретинопатию, глаукому и пигментный ретинит. В этой диссертации использовались различные методы для анализа сигналов ЭРГ, включая методы временной области, частотной области и частотно-временной области. Процесс начался с очистки базы данных сигналов и предварительной обработки извлеченных сигналов. Затем были вычислены стандартные компоненты сигнала, включая a- и b-волны и неявное время, и был проведен анализ сигналов во временной области. Анализ во временной области включал изучение амплитуд и задержек различных компонентов волны, что может дать представление о функционировании различных типов клеток сетчатки. Корреляционный анализ также проводился для изучения взаимосвязи между возрастом пациентов и компонентами сигнала, результаты которого показывают очень слабую корреляцию между возрастом и компонентами, с некоторой значительной корреляцией между отдельными компонентами. В частотной области преобразование Фурье использовалось для извлечения частот сигналов для анализа. Частотное содержимое сигналов ЭРГ может раскрыть информацию о базовых физиологических процессах и потенциальных отклонениях. Однако из-за инвариантной во времени природы частотной области делать выводы, основанные исключительно на этом анализе, может быть сложно. Для анализа частотно-временной области использовалось кратковременное преобразование Фурье (STFT) вместе с анализом спектрограмм. STFT позволяло изучить, как частотное содержимое сигналов менялось с течением времени, обеспечивая более полное представление динамики сигнала. Кроме того, признаки извлекались с использованием различных окон и размеров окон для обучения классификатора машинного обучения с целью классификации сигналов. Вычисленные спектрограммы также использовались для обучения моделей глубокого обучения с различными архитектурами, и результаты сравнивались на основе используемых окон. Результаты показывают, что нет заметной корреляции между возрастом и другими компонентами сигнала во временной области. Это говорит о том, что возраст сам по себе не может быть надежным предиктором характеристик сигнала ERG. В частотной области делать выводы, основанные исключительно на частотном содержании, оказалось сложно из-за инвариантной во времени природы анализа. Более того, очевидно, что размеры окон оказывают более существенное влияние на результирующие признаки по сравнению с функциями окна. Большие размеры окон обеспечивают улучшенное разрешение по частоте, в то время как меньшие окна обеспечивают более высокое разрешение по времени. Это означает, что разрешение по времени и частоте играет более существенную роль в формировании результирующих признаков, чем обработка сигнала, выполняемая самой функцией окна. Анализ сигналов ERG с использованием различных методов, включая методы временной области, частотной области и частотно-временной области, дает ценную информацию о функции сетчатки и потенциальных расстройствах. Сочетание этих подходов, наряду с методами извлечения признаков и машинного обучения, предлагает комплексную структуру для понимания и интерпретации сигналов ERG. Однако тщательное рассмотрение таких факторов, как размеры окон и компромиссы разрешения, имеет решающее значение для получения значимых и точных результатов. / Electroretinography (ERG) is a non-invasive way of measuring the electrical activity of the retina with the help of light stimulation. ERG signals contain several different components which can be used to diagnose various retinal disorders. Some of these disorders include cone and rod related dystrophies, age-related macular degeneration, diabetic retinopathies, glaucoma and retinitis pigmentosa. In this thesis, various methods were utilized to analyze ERG signals, including time-domain, frequency-domain, and time-frequency domain techniques. The process began with cleaning the signals database and preprocessing the extracted signals. Next, standard signal components including the a- and b-waves and implicit times were computed, and time-domain analysis was conducted on the signals. The time-domain analysis involved examining the amplitudes and latencies of the different wave components, which can provide insights into the functioning of different retinal cell types. Correlation analysis was also conducted to examine there’s relationship between the patients’ age and the signal components which the results show very little correlation between the age and the components, with some significant correlation between the individual components. In the frequency domain, Fourier Transform was used to extract signal frequencies for analysis. The frequency content of the ERG signals can reveal information about the underlying physiological processes and potential abnormalities. However, due to the time-invariant nature of the frequency domain, drawing conclusions based solely on this analysis can be challenging. For time-frequency domain analysis, short-time Fourier transform (STFT) was employed along with spectrogram analysis. The STFT allowed for the examination of how the frequency content of the signals evolved over time, providing a more comprehensive representation of the signal dynamics. Additionally, features were extracted using different windows and window sizes for machine learning classifier training to classify the signals. The spectrograms computed were also used to train deep learning models with different architectures, and the results were compared based on the windows used. The findings indicate that there is no discernible correlation between age and other signal components in the time domain. This suggests that age alone may not be a reliable predictor of ERG signal characteristics. In the frequency domain, drawing conclusions based solely on the frequency content proved challenging due to the time-invariant nature of the analysis. Moreover, it is evident that window sizes have a more significant impact on the resulting features compared to window functions. Larger window sizes yield improved frequency resolution, while smaller windows offer higher time resolution. This implies that the time and frequency resolution play a more substantial role in shaping the resulting features than the signal processing performed by the window function itself. The analysis of ERG signals using various techniques, including time-domain, frequency-domain, and time-frequency domain methods, provides valuable insights into retinal function and potential disorders. The combination of these approaches, along with feature extraction and machine learning techniques, offers a comprehensive framework for understanding and interpreting ERG signals. However, careful consideration of factors such as window sizes and resolution trade-offs is crucial for obtaining meaningful and accurate results.