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Biomedical subjects

Nagaaki Ohyama

Publications and source records attributed to Nagaaki Ohyama.

7 recordsLinked to original sources

Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance.

In this study, the digital transformation (digital staining) of the 16-band multispectral image of a hematoxylin and eosin (HE) stained pathological specimen to its Masson's trichrome (MT) stained counterpart is addressed. The digital staining procedure involves the classification of the various H&E-stained tissue components and then the transformation of their transmittance spectra to their equivalent MT-stained transmittance configurations. Combination of transmittance classifiers were designed to classify the various tissue components found in the multispectral images of an HE-stained specimen, e.g. nucleus, cytoplasm, red blood cell (RBC), fibrosis, etc.; while pseudo-inverse method was used to obtain the transformation matrices that would translate the transmittance spectra of the classified HE-stained multispectral pixels to their MT-stained configurations. To generate the digitally stained image, weighting factors, which were based on the classifiers beliefs, were introduced to the generated transformation matrices. Initial results of our experiments on liver specimens show the viability of multispectral imaging (MSI) to implement a digital staining framework in the pathological context.

Diagnosis, Computer-Assisted↗

Transaxial system models for jPET-D4 image reconstruction.

A high-performance brain PET scanner, jPET-D4, which provides four-layer depth-of-interaction (DOI) information, is being developed to achieve not only high spatial resolution, but also high scanner sensitivity. One technical issue to be dealt with is the data dimensions which increase in proportion to the square of the number of DOI layers. It is, therefore, difficult to apply algebraic or statistical image reconstruction methods directly to DOI-PET, though they improve image quality through accurate system modelling. The process that requires the most computational time and storage space is the calculation of the huge number of system matrix elements. The DOI compression (DOIC) method, which we have previously proposed, reduces data dimensions by a factor of 1/5. In this paper, we propose a transaxial imaging system model optimized for jPET-D4 with the DOIC method. The proposed model assumes that detector response functions (DRFs) are uniform along line-of-responses (LORs). Then each element of the system matrix is calculated as the summed intersection lengths between a pixel and sub-LORs weighted by a value from the DRF look-up-table. 2D numerical simulation results showed that the proposed model cut the calculation time by a factor of several hundred while keeping image quality, compared with the accurate system model. A 3D image reconstruction with the on-the-fly calculation of the system matrix is within the practical limitations by incorporating the proposed model and the DOIC method with one-pass accelerated iterative methods.

Brain↗

Multiple-discriminant analysis for light-scattering spectroscopy and imaging of two-layered tissue phantoms.

We propose a new method for enhancing the sensitivity of the reflectance spectrum to the scattering feature of the superficial tissue layer. This method is based on multiple-discriminant analysis in the eigensubspace of the spectrum. Considering the application of scattering imaging, we evaluated this method by performing multispectral imaging of two-layered tissue phantoms. A color map converted from the spectral reflectance corresponds well to variations in the size of the scattering in the first layer.

Discriminant Analysis↗

Nonlinear estimation of spectral reflectance based on Gaussian mixture distribution for color image reproduction.

Nonlinear estimation method of spectral reflectance from camera responses is proposed. The proposed method minimizes the mean square error of spectral reflectance when the reflectance can be regarded as a random sequence of Gaussian mixture distribution. In computer simulations, 168 samples of spectral reflectance from a color chart are estimated from their image signals obtained by three- and six-band cameras. It is confirmed that the proposed method improves the accuracy in comparison with the conventional Wiener estimation method.

Journal Article↗

Fast determination method of cerebral metabolic rate images of glucose using dynamic PET data.

Measurement of the rate constant parameters of the tracer 18F-FDG, used with positron emission tomography (PET) to determine the cerebral metabolic rate of glucose (CMRGlc), can provide a clear understanding of the physiological processes in the human brain. At present, the methods that are widely used to obtain CMRGlc, such as nonlinear least squares (NLS), first require the reconstruction of a time sequence of images. The reconstruction of these images requires a large amount of computation, especially in 3D Depth-of Interaction PET (DOI-PET), and the nonlinear based methods also require a large amount of computation. In this paper, we propose a fast parametric image reconstruction method for 18F-FDG dynamic PET studies. In our method a deconvolving process is first employed on the time sequential projection data to remove the effect of the measured plasma time activity. The deconvolved terms are integrated over three different time intervals and the parameters for determining CMRGlc can be obtained analytically. Our method requires only three reconstructing processes and reduces the computational demand to estimate CMRGlc. The algorithm performance is evaluated using a digital phantom and a clinical data set and the results show that the proposed method produces images with the same or better quality as the images from the NLS method, with much less computation compared to the NLS method.

Algorithms↗

[Algebraic 2D PET image reconstruction using depth-of-interaction information]

Recently a high-performance PET scanner, which measures depth-of-interaction (DOI) information, is being developed for molecular imaging. DOI measurement of multi-layered thin crystals can improve spatial resolution and scanner sensitivity simultaneously. In this paper, we apply an algebraic image reconstruction method to 2-dimensional (2D) DOI-PET scanners using accurate system modeling, in order to evaluate the effects of using DOI information on PET image quality. Algebraic image reconstruction methods have been successfully used to improve PET image quality, compared with the conventional filtered backprojection method. The proposed method is applied to simulated data for a small 2D DOI-PET scanner. The results show that accurate system modeling improves spatial resolution without noise emphasis, and that DOI information improves uniformity of spatial resolution.

Journal Article↗

Appearance of enhanced tissue features in narrow-band endoscopic imaging.

This study was performed to examine the usefulness of medical endoscopic imaging utilizing narrow-band illumination. The contrast between the vascular pattern and the adjacent mucosa of the underside of the human tongue was measured using five narrow-band illuminations and three broadband illuminations. The results demonstrate that the pathological features of a vascular pattern are dependent on the center wavelength and the bandwidth of illumination. By utilizing narrow-band illumination of 415+/-30 nm, the contrast of the capillary pattern in the superficial layer was markedly improved. This is an important benefit that is difficult to obtain with ordinary broadband illumination. The appearances of capillary patterns on color images were evaluated for three sets of filters. The narrow, band imaging (NBI) filter set (415+/-30 nm, 445+/-30 nm, 500+/-30 nm) was selected to achieve the preferred appearance of the vascular patterns for clinical tests. The results of clinical tests in colonoscopy and esophagoscopy indicated that NBI will be useful as a supporting method for observation of the endoscopic findings of early cancer.

Barrett Esophagus↗