Yoko Kawamura

Callosal Shapes at the Midsagittal Plane: MRI Differences of Normal Males, Normal Females, and GID

We investigated differences in corpus callosum shape at the midsagittal plane using MRI for different subjects: normal males, normal females, and subjects with gender identity disorder (GID). We first represented callosal shapes with Fourier descriptors of callosal contours. Using linear support vector machines with soft-margin, we next determined a hyperplane that separates normal males and females most optimally in the vector space spanned by Fourier descriptors. We then proposed a measure that has prominent sex difference: it is defined as the coordinate of a given callosal shape on the subspace orthogonal to the obtained hyperplane. Use of the measure provides discrimination of someones sex with 74.17% accuracy. We further showed that the value of the measure for GID more strongly reflects their mental sex, i.e. gender, than their physical sex

Estimation of carotid diameter with heartbeat on longitudinal B-mode ultrasonic images

Arteriosclerosis, i.e. degrading arterial elasticity, causes cerebral infarction and myocardial infarction. Premonition of arteriosclerosis is important because arteriosclerosis is never cured completely. We therefore propose a method to track the carotid diameter to evaluate the initial carotid elasticity accompanied with a persons heartbeat using the longitudinal B-mode ultrasonic images. If the diameter of carotid artery can be accurately estimated, it is possible to implies for initial inference of the presence of arteriosclerosis. In future studies, it has to be assessed with comparisons to anaother established method.

Estimation of Carotid Stiffness Using Ultrasonic Dynamic Images for Evaluating the Degree of Arteriosclerosis

Some methods for evaluating the degree of arteriosclerosis utilizing the magnitude of systaltic movement of carotid artery have been proposed. The magnitude of carotid movement depends on the stiffness of surrounding tissues around carotid artery as well as the stiffness of carotid artery itself. Therefore, accurate criterion for the degree of arteriosclerosis cannot be obtained only by observing the magnitude of carotid movement. This study proposes an estimation method of the “self-”stiffness of carotid artery by excluding influence of the stiffness of surrounding tissues. In the proposed method, the systaltic movement of surrounding tissues as well as carotid artery is tracked by an optical flow method using ultrasonic B-mode images drawing the cross section of carotid artery.

Propagation Route Estimation of Heart Sound through Simultaneous Multi-site Recording on the Chest Wall

While vibration source of the heart sound has been well-studied, the propagation route of the heart sound on the chest wall has not been clarified. In this study, we first measured the heat sound simultaneously at 64 positions on the chest wall of healthy subjects using 64 small accelerometers. We next calculated the delay times in the vibration propagation between all possible pair of neighboring positions. We proposed the estimation method for the propagation route of heart sound vibration on the chest wall by solving the shortest path problem in the graph-network theory only using such neighboring delay times. Applying to the recorded heart sound signals, we can obtain the estimated propagation route originated at the cardiac apex for the first heart sound, and that originated at aortic valve for the second heart sound.

Premonitory Symptom of Septic Shock in Heart Rate Variability

Delay of administering therapy increases the mortality of septic patients. Diagnosing sepsis, however, depends on the decision of an experienced specialist of whether to perform a blood test. Therefore, we believe that a real-time, non-invasive monitoring system for sepsis is useful to promote early intervention. Heart rate variability (HRV), a measure of autonomic nervous system (ANS) activity, has been suggested as an indicator of septic shock. When analyzing electrocardiograms of patients admitted in the intensive care unit (ICU), an important challenge is to distinguish HRV originating in the ANS from other factors such as arrhythmia. A stochastic model is used in this study to extract HRV caused by ANS automatically. Applying the proposed process before HRV estimation, we identified a distinctive V-shaped temporal pattern in HRV as a signal of sepsis. Our investigation continues to explain how that temporal pattern is useful to develop a real-time sepsis monitoring system for sepsis occurrence.

Ultrasound image-based estimation system for arteriosclerosis of in vivo blood vessels

With aging, the mechanical properties of a blood vessel degrade; its strength and elongation decreases. However, its stiffness (stress/strain) increases. Also the rate of hardening of the vessel depends on the individual. It is an urgent task to establish an inspection technique for strength parameters as hardening progresses. This report presents such a technique for estimating sclerosis of in vivo blood vessel with ultrasound B-mode image. The method is based on in vivo stiffness (Eth) calculated from variations in vessel diameter with changes in systolic and diastolic blood pressures. In addition, we obtained a correlation between Eth and strength (σu) from the results of tensile and internal pressure tests using some animal model and human artery specimens. Therefore, we can estimate in vivo Eth and σu of an artery using B-mode image and an associated correlation curve. To simplify the measurement of changes in diameter, prototype software was developed. To examine the validity of this technique, clinical data was collected at some hospitals. The results indicated that Eth and σu are useful symptom indices for arteriosclerosis, particularly for identifying the beginning of sclerosis in patients in their early twenties.

Novel technique for visualizing heart motion without using ultrasonic cardiography

A novel technique for imaging heart motion has been developed. This is based on measurement of minute vibration of the chest surface using 64 sensors (63- acceleration sensor and one ECG) and image processing. The chest surface vibration included three or four frequency bands. One frequency band was inaudible sound using auscultation, under 20 Hz. The results showed that clear contour image of the heart from the data of 1-50 Hz band and also contraction/expansion of atrioventricular and ventricle and location of valves were visualized from the data of all frequency bands. It is concluded that the technique is applicable to examine heart function for 24-hour and irregular heart motion.

Medical image processing and computer-aided detection/diagnosis (CAD)

Computer-aided detection/diagnosis (CAD) is emerging as an innovative interdisciplinary technology for medical service. The traditional concept of automated computer diagnosis is encountered with a significant barrier because computerized medical systems cannot fully replace human doctors with the comparable level of performance. By contrast, CAD is becoming widely adopted in clinical work because it offers complementary computing power to enhance doctors competence for medical examination. 4 state-of-the-art CAD technologies were presented in the special session of medical image processing and CAD at ICCH 2012 as reported in this short paper. Those technologies will be briefly introduced here to show the current trend of development of CAD and to demonstrate how CAD helps in medical care.

Septic Shock Prediction by Real Time Monitoring of Heart Rate Variability

We propose a method for septic shock prediction by real time monitoring of heart rate variability (HRV) for patients in intensive care unit (ICU). An objective criterion that is related to septic occurrence and can be measured automatically in real time is required to detect septic occurrence. Although HRV is a candidate of such criteria, an automatic estimation of HRV has been difficult because there are many arrhythmias in ICU patients. In this study, we employed a stochastic model on R-R interval series, namely heartbeat interval series, in order to detect abnormal heartbeats in normal R-R interval series automatically. Abnormal heartbeats and very low frequency components are eliminated from R-R series by using the stochastic model. Applying the elimination process before HRV estimation, we identified a distinctive V-shaped temporal pattern in HRV series before septic shock was occurred. The V-shaped pattern is applicable as a signal of septic occurrence. We finally propose a real-time monitoring for sepsis occurrence by using the V-shaped pattern in HRV.

Visualisation of heart sounds and motion using multi-channel sensor

As there are various difficulties associated with auscultation techniques, we have devised two techniques for visualising heart sound and motion to assist in the understanding of heartbeat for both doctors and patients that: To overcome difficulties in auscultation, these techniques can be applied to the detection of heart disease and to the digital database management of the auscultation examination.