Validated Filter-Based Photoreceptor Count Algorithm on Retinal Heidelberg High Magnification Module™ Images in Healthy and Pathological Conditions

Recently introduced, the Heidelberg Engineering™ high magnification module enables in vivo visualization of cone photoreceptor cells. Currently, a reliable analysis of cone mosaic on high magnification module images is hindered by an unfavorable signal-to-noise ratio. In this paper, we describe how a novel high magnification module high-pass filter may enhance cone signals in healthy participants and patients. We compared the cone counts of our filter-based algorithm to the counts of two human graders. We found a good to excellent intragrader and intergrader correlation in both patients and healthy participants. We identified a good correlation between the average cone counts of both graders and high-pass filter cone counts in patients and healthy participants. We observed no significant difference between manual and filter-based counts via the Bland–Altman analysis. In conclusion, a quantitative cone analysis on high magnification module images is feasible manually by human graders and automatically by a filter-based algorithm. However, larger datasets are needed to improve repeatability and consistency by training human graders.

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Application of Butterworth high pass filter as an approximation of Wood Anderson seismometer frequency response to earthquake signal recording

ACTA IMEKO ◽

10.21014/acta_imeko.v9i5.1005 ◽

2020 ◽

Vol 9 (5) ◽

pp. 379

Author(s):

Hamidatul Husna Matondang ◽

Endra Joelianto ◽

Sri Widiyantoro

Keyword(s):

Frequency Response ◽

Signal To Noise Ratio ◽

Cutoff Frequency ◽

Maximum Amplitude ◽

Second Order ◽

Pass Filter ◽

High Pass Filter ◽

Local Earthquake ◽

Seismic Magnitude ◽

High Pass

The method for generating maximum amplitude and signal to noise ratio values by using second order high pass Butterworth filter on local seismic magnitude scale calculations is proposed. The test data are signals from local earthquake that have been occurred in Sunda Strait on April 8th 2012. Based on the experimental results, a 8 Hz cutoff frequency and a gain of 2200 of second order Butterworth high pass filter as an approach to simulating the frequency response of Wood Anderson seismometer can provide maximum amplitude value, SNR, and the magnitude better than simulated Wood Anderson frequency response.

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Influence of High Pass Filter Settings on Motor Evoked Potentials

Frontiers in Neuroscience ◽

10.3389/fnins.2021.665258 ◽

2021 ◽

Vol 15 ◽

Author(s):

Petyo Nikolov ◽

Shady S. Hassan ◽

Alfons Schnitzler ◽

Stefan J. Groiss

Keyword(s):

Evoked Potentials ◽

Motor Evoked Potentials ◽

Signal To Noise Ratio ◽

Notch Filter ◽

Pass Filter ◽

Low Pass Filter ◽

High Pass Filter ◽

Low Pass ◽

High Pass ◽

Selection Of

ObjectiveMotor evoked potentials (MEP), obtained by transcranial magnetic stimulation (TMS) are a common tool in clinical research and diagnostic. Nevertheless, reports regarding the influence of filter settings on MEP are sparse. Here, we compared MEP amplitudes and signal to noise ratio (SNR) using multiple high pass filter (HPF) and notch filter settings.Materials and MethodsTwenty healthy subjects were enrolled in the study. Recruitment curves were obtained with HPF settings varied at 10, 20, 50, and 100 Hz. The four HPF settings were tested both with and without 50 Hz active notch filter. Low pass filter was kept constant at 5 kHz.ResultsMEP amplitudes with HPF at 10 and 20 Hz were significantly higher than at 100 Hz, regardless of the notch filter. However, SNR did not differ among HPF settings. An active notch filter significantly improved SNR.ConclusionThe reduction in MEP amplitudes with HPF above 20 Hz may be due to noise reduction, since the different HPF conditions did not alter SNR. Thus, higher HPF above 50 Hz may be an option to reduce noise, the use of a notch filter may even improve SNR.SignificanceOur findings are relevant for the selection of filter settings and might be of importance to any researcher who utilizes TMS-MEP.

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Metode High-Pass Filter Dan Fast Fourier Transform Untuk Perbaikan Citra Telapak Tangan

Techno Com ◽

10.33633/tc.v20i4.5262 ◽

2021 ◽

Vol 20 (4) ◽

pp. 601-612

Author(s):

Mhd Furqan ◽

- Sriani ◽

Muhammad Akbar Ramadhan Tanjung

Keyword(s):

Fourier Transform ◽

Fast Fourier Transform ◽

Mean Square Error ◽

Signal To Noise Ratio ◽

Mean Square ◽

Signal To Noise ◽

Pass Filter ◽

High Pass Filter ◽

Noise Ratio ◽

High Pass

Telapak tangan sering digunakan sebagai sumber penelitian dibidang sistem biometrik karena mempunyai karakteristik seperti sidik jari. Selain itu, telapak tangan juga mudah didapatkan dan dapat diperoleh dari citra yang memiliki resolusi rendah. Namun, selain itu juga sebuah citra telapak tangan akan dapat mengalami penurunan terhadap kualitasnya. Untuk itu dilakukanlah sebuah tahap yang dikenal dengan perbaikan kualitas citra, dimana bidang ini merupakan tahap awal dari pengolahan citra digital. Dalam penelitian ini penggunaan metode dalam perbaikan citra difokuskan untuk menajamkan citra telapak tangan dengan menggunakan high pass filter dan filter fast fourier transform, dimana sebelumnya citra tersebut telah diolah dengan menggunakan histogram ekualisasi untuk meningkatkan kontras citra telapak tangan. Setelah dilakukan pengujian terhadap 30 sampel citra. Dengan menilai error pada MSE (Mean Square Error) dan PSNR (Peak Signal to Noise Ratio) dari citra hasil rekonstruksi, hasil pengujian menunjukkan bahwa penggunaan high pass filter dengan koefisien=1 menghasilkan citra yang lebih baik dimana nilai rata-rata MSE=7,064544(dB) dan PSNR=40,01314(dB) daripada menggunakan high-pass filter dengan koefisien=0. Sedangkan pada fast fourier transform dengan menggunakan Ideal High-Pass Filter (IHPF) mampu menghasilkan citra rekonstruksi yang lebih baik dengan rerata MSE=9,354056(dB) dan PSNR=38,537046(dB) dari pada menggunakan butterworth high-pass filter (BHPF) dan gaussian high-pass filter (GHPF)

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