Retinal blood vessel segmentation using Otsu thresholding with principal component analysis

Dash, Jyotiprava; Bhoi, Nilamani

doi:10.1109/icisc.2018.8398938

Cited by 16 publications

(14 citation statements)

References 9 publications

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“…The result of this spatially filtered MIP was then subtracted from the original MIP. The image was then normalized between 0 and 1, followed by a contrast limited adaptive histogram equalization (CLAHE) process to increase local contrast in the image by making the vessel intensities more uniform .…”

Section: Methodsmentioning

confidence: 99%

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

Karrobi

Tank

Tabassum

et al. 2019

Journal of Biophotonics

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Diffuse optical imaging (DOI) techniques provide a wide‐field or macro assessment of the functional tumor state and have shown substantial promise for monitoring treatment efficacy in cancer. Conversely, intravital microscopy provides a high‐resolution view of the tumor state and has played a key role in characterizing treatment response in the preclinical setting. There has been little prior work in investigating how the macro and micro spatial scales can be combined to develop a more comprehensive and translational view of treatment response. To address this, a new multiscale preclinical imaging technique called diffuse and nonlinear imaging (DNI) was developed. DNI combines multiphoton microscopy with spatial frequency domain imaging (SFDI) to provide multiscale data sets of tumor microvascular architecture coregistered within wide‐field hemodynamic maps. A novel method was developed to match the imaging depths of both modalities by utilizing informed SFDI spatial frequency selection. An in vivo DNI study of murine mammary tumors revealed multiscale relationships between tumor oxygen saturation and microvessel diameter, and tumor oxygen saturation and microvessel length (|Pearson's ρ| ≥ 0.5, P < 0.05). Going forward, DNI will be uniquely enabling for the investigation of multiscale relationships in tumors during treatment.

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Section: Methodsmentioning

confidence: 99%

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

Karrobi

Tank

Tabassum

et al. 2019

Journal of Biophotonics

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“…Proses awal dilakukan dengan mengambil green channel pada citra retina dengan tujuan mendapatkan hasil pembuluh darah yang lebih jelas. Jika dibandingkan dengan red channel dan blue channel hasil green channel menghasilkan citra yang paling baik, maka green channel dipilih digunakan dalam proses ini [5]. Setelah itu dilakukan pengubahan piksel warna menjadi Grayscale.…”

Section: B Pre-processingunclassified

“…CLAHE diharapkan menampilkan fitur yang tersembunyi dengan menerapkan pemerataan histogram untuk tiap-tiap nilai piksel. CLAHE memberikan nilai batas maksimal tinggi sebuah histogram dinamakan clip limit yang akan membagi citra menjadi beberapa bagian kecil dengan ukuran identik sehingga histogram dari gambar luaran sesuai dengan histogram yang ditunjukkan oleh parameter ditribusi [2], [5], [8]. Perhitungan clip limit mengunakan persamaan (1):…”

Section: B Pre-processingunclassified

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Variasi Thresholding untuk Segmentasi Pembuluh Darah Citra Retina

Desiani

Zayanti

Primartha

et al. 2021

JEPIN

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Segmentasi pembuluh darah pada retina diperlukan pada deteksi dini penyakit Diabetic Retinopathy pada citra retina. Penelitian ini menggunakan tiga tahapan yaitu pre-processing, segmentasi dan post-processing yang akan membandingkan hasil dari 3 metode segmentasi yang menggunakan nilai Thresholding yaitu Adaptive Thresholding, Binary Thresholding, dan Otsu Thresholding. Hasil pengujian terhadap tiga metode yang digunakan menunjukan bahwa metode Binary Thresholding mendapat rata-rata akurasi, sensitivitas dan spesifisitas tertinggi yaitu 95%, 58%, 98%. Untuk Adaptive Thresholding mendapat rata-rata akurasi sebesar 91%, sensitivitas 36%, spesititiftas 97%. Dan metode Otsu Thresholding mendapatkan rata-rata akurasi 86%, sensitivitas 22%, dan spesifisitas 90%. Dari hasil ketiga metode ini dapat dilihat akurasi yang dihasilkan oleh metode Thresholding sudah sangat baik dalam melakukan segmentasi citra, tetapi nilai sensitivitas dari masing-masing metode Thresholding masih rendah. Hal ini dapat disimpulkan metode Thresholding masih sulit mendapatkan lebih banyak fitur pembuluh darah pada citra retina.

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“…In this CLAHE all pixels adjacent to all functions will be converted [14]. This CLAHE is different from AHE because CLAHE limits the contrast, uses the maximum value on the clip and returns it to the gray value [19].…”

Section: E Clahe(contrast Limited Adaptive Histogram Equalization)mentioning

confidence: 99%

Improving Retinal Image Quality Using the Contrast Stretching, Histogram Equalization, and CLAHE Methods with Median Filters

Erwin¹

2020

IJIGSP

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This paper performs three different contrast testing methods, namely contrast stretching, histogram equalization, and CLAHE using a median filter. Poor quality images will be corrected and performed with a median filter removal filter. STARE dataset images that use images with different contrast values for each image. For this reason, evaluating the results of the three parameters tested are; MSE, PSNR, and SSIM. With the gray level scale image and contrast stretching which stretches the pixel value by stretching the stretchlim technique with the MSE result are 9.15, PSNR is 42.14 dB, and SSIM is 0.88. And the HE method and median filter with the results of the average value of MSE is 18.67, PSNR is 41.33 dB, and SSIM is 0.77. Whereas for CLAHE and median filters the average yield of MSE is 28.42, PSNR is 35.30 dB, and SSIM is 0.86. From the test results, it can be seen that the proposed method has MSE and PSNR values as well as SSIM values.

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Retinal blood vessel segmentation using Otsu thresholding with principal component analysis

Cited by 16 publications

References 9 publications

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

Variasi Thresholding untuk Segmentasi Pembuluh Darah Citra Retina

Improving Retinal Image Quality Using the Contrast Stretching, Histogram Equalization, and CLAHE Methods with Median Filters

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