Diagnostic techniques for improved segmentation, feature extraction, and classification of malignant melanoma.

A typical diagnosis of malignant melanoma involves three major steps: segmentation of a lesion from the input color image, feature extraction from the separated lesion, and classification to distinguish malignant from benign melanomas based on features obtained. We suggest new methods for segmentation, feature extraction, and classification compared. We replaced edge-imfill method with U-Otsu method for segmentation, the previous features with new features for the criteria ABCD (asymmetry, border irregularity, color variegation, diameter) criteria, and the median thresholding with weighted receiver operating characteristic thresholding for classification.

An inversion of the conical Radon transform arising in the Compton camera with helical movement.

Since the Compton camera was first introduced, various types of conical Radon transforms have been examined. Here, we derive the inversion formula for the conical Radon transform, where the cone of integration moves along a curve in three-dimensional space such as a helix. Along this three-dimensional curve, a detailed inversion formula for helical movement will be treated for Compton imaging in this paper.

A mathematical analysis of the ABCD criteria for diagnosing malignant melanoma.

The medical community currently employs the ABCD (asymmetry, border irregularity, color variegation, and diameter of the lesion) criteria in the early diagnosis of a malignant melanoma. Although many image segmentation and classification methods are used to analyze the ABCD criteria, it is rare to see a study containing mathematical justification of the parameters that are used to quantify the ABCD criteria. In this paper, we suggest new parameters to assess asymmetry, border irregularity, and color variegation, and explain the mathematical meaning of the parameters.

Electrochemical detection of high-sensitivity CRP inside a microfluidic device by numerical and experimental studies.

The concentration of C-reactive protein (CRP), a classic acute phase plasma protein, increases rapidly in response to tissue infection or inflammation, especially in cases of cardiovascular disease and stroke. Thus, highly sensitive monitoring of the CRP concentration plays a pivotal role in detecting these diseases. Many researchers have studied methods for the detection of CRP concentrations such as optical, mechanical, and electrochemical techniques inside microfluidic devices.

Development of compression-controlled low-level laser probe system: towards clinical application.

Various physico-chemical tissue optical clearing (TOC) methods have been suggested to maximize photon density in tissue. In order to enhance photon density, a compression-controlled low-level laser probe (CCLLP) system was developed by utilizing the principle of mechanical tissue compression. Negative compression (NC) was applied to the laser probes built in various diameters and simultaneously the laser was irradiated into ex-vivo porcine skin samples.

Neurofeedback-based motor imagery training for brain-computer interface (BCI).

In the present study, we propose a neurofeedback-based motor imagery training system for EEG-based brain-computer interface (BCI). The proposed system can help individuals get the feel of motor imagery by presenting them with real-time brain activation maps on their cortex. Ten healthy participants took part in our experiment, half of whom were trained by the suggested training system and the others did not use any training.

Enhancement of light propagation depth in skin: cross-validation of mathematical modeling methods.

Various techniques to enhance light propagation in skin have been studied in low-level laser therapy. In this study, three mathematical modeling methods for five selected techniques were implemented so that we could understand the mechanisms that enhance light propagation in skin. The five techniques included the increasing of the power and diameter of a laser beam, the application of a hyperosmotic chemical agent (HCA), and the whole and partial compression of the skin surface.

Evaluation of laser beam profile in soft tissue due to compression, glycerol, and micro-needling.

Background And Objectives: Various methods have been suggested to enhance photon density in biological tissues in an attempt to maximize the efficacy of laser therapy. In this study, the effects of tissue compression, glycerol, and micro-needling methods on the laser beam profile (LBP) were investigated by quantitatively evaluating the spatial distribution of subsurface tissue photon density.

Study Design/materials And Methods: The LBP in tissue was obtained by imaging the laser beam transmitted through ex vivo porcine skin samples.

Regularization of DT-MR images using a successive Fermat median filtering method.

Tractography using diffusion tensor magnetic resonance imaging (DT-MRI) is a method to determine the architecture of axonal fibers in the central nervous system by computing the direction of greatest diffusion in the white matter of the brain. To reduce the noise in DT-MRI measurements, a tensor-valued median filter, which is reported to be denoising and structure preserving in the tractography, is applied. In this paper, we proposed the successive Fermat (SF) method, successively using Fermat point theory for a triangle contained in the two-dimensional plane, as a median filtering method.

A study on the comparison of median filter regularization methods in diffusion tensor MRI.

Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) is a method which makes it possible to study non-invasively the architecture of axonal fibers in the central nervous system. Since eigenvectors obtained from DT-MRI usually contain noise, the calculated vector directions may be deviated from the real fiber orientation. Therefore, noise errors can be accumulated as fiber tract becomes longer in tractography of DT-MRI.