Kazuya Nakano

SIGNIFICANCE: Evaluation of biological chromophore levels is useful for detection of various skin diseases, including cancer, monitoring of health status and tissue metabolism, and assessment of clinical and physiological vascular functions. Clinically, it is useful to assess multiple different chromophores in vivo with a single technique or instrument. AIM: To investigate the possibility of estimating the concentration of four chromophores, bilirubin, oxygenated hemoglobin, deoxygenated hemoglobin, and melanin from diffuse reflectance spectra in the visible region. APPROACH: A new diffuse reflectance spectroscopic method based on the multiple regression analysis aided by Monte Carlo simulations for light transport was developed to quantify bilirubin, oxygenated hemoglobin, deoxygenated hemoglobin, and melanin. Three different experimental animal models were used to induce hyperbilirubinemia, hypoxemia, and melanogenesis in rats. RESULTS: The estimated bilirubin concentration increased after ligation of the bile duct and reached around 18  mg/dl at 50 h after the onset of ligation, which corresponds to the reference value of bilirubin measured by a commercially available transcutaneous bilirubin meter. The concentration of oxygenated hemoglobin and that of deoxygenated hemoglobin decreased and increased, respectively, as the fraction of inspired oxygen decreased. Consequently, the tissue oxygen saturation dramatically decreased. The time course of melanin concentration after depilation of skin on the back of rats was indicative of the supply of melanosomes produced by melanocytes of hair follicles to the growing hair shaft. CONCLUSIONS: The results of our study showed that the proposed method is capable of the in vivo evaluation of percutaneous bilirubin level, skin hemodynamics, and melanogenesis in rats, and that it has potential as a tool for the diagnosis and management of hyperbilirubinemia, hypoxemia, and pigmented skin lesions.

Double random phase encoding (DRPE) is vulnerable to known-plaintext attacks (KPAs) based on phase retrieval algorithms. We previously analyzed DRPE resistance to KPA cryptanalysis with multiple known plaintext–ciphertext image pairs and obtained secret keys at a higher probability rate than when performing KPA cryptanalysis using one known image pair. However, the robustness of KPA in the presence of noise or occlusion in DRPE is unclear. We analyzed KPA properties in relation to DRPE when white Gaussian noise was gradually added to the Fourier amplitude or phase of a known ciphertext complex amplitude image. Additionally, we analyzed KPA properties when the Fourier phase of the known ciphertext image was gradually occluded by zero-valued pixels. The results showed that KPAs performed using multiple known plaintext–ciphertext image pairs were largely affected by noise added to the Fourier phase and thus are not always a strong tool for DRPE cryptanalysis.

Retinitis pigmentosa (RP) is a group of genetic disorders, characterized by degeneration of photoreceptor cells which is the main cause of choroidal thinning. It is one of the leading causes of blindness worldwide. Thus, an investigation of choroidal changes is required for a better understanding of disease and diagnosis of RP. In this paper, we propose an automatic technique for measuring the choroidal parameters in optical coherence tomography (OCT) images of eyes with RP. The parameters include the total choroidal area (TCA), luminal area (LA), stromal area (SA), and choroidal thickness (CT). We applied our recently proposed, dense dilated U-Net segmentation model, called ChoroidNET, for segmenting the choroid layer and choroidal vessels for our RP dataset. Choroid segmentation is an important task since the measurement results depend on it. Comparison with other state-of-the-art models shows that ChoroidNET provides a better quantitative and qualitative segmentation of the choroid layer and choroidal vessels. Next, we measure the choroidal parameters based on the segmentation results of ChoroidNET. The proposed method achieves high reliability with an intraclass correlation coefficient (0.961, 0.940, 0.826, 0.916) for TCA, LA, SA, and CT, respectively.

Understanding the changes in choroidal thickness and vasculature is important to monitor the development and progression of various ophthalmic diseases. Accurate segmentation of the choroid layer and choroidal vessels is critical to better analyze and understand the choroidal changes. In this study, we develop a dense dilated U-Net model (ChoroidNET) for segmenting the choroid layer and choroidal vessels in optical coherence tomography (OCT) images. The performance of ChoroidNET is evaluated using an OCT dataset that contains images with various retinal pathologies. Overall Dice coefficient of 95.1 +/- 0.4 and 82.4 +/- 2.4 were obtained for choroid layer and vessel segmentation, respectively. Comparisons show that among state-of-the-art models, ChoroidNET, which produces results that are consistent with ground truths, is the most robust segmentation framework.