Abstract: An apparatus and a method for processing signal are provided. The signal processing apparatus comprises an input interface and a processing unit. The input interface receives smoothing parameters and a to-be-separated signal. The processing unit establishes an upper extreme envelope and a lower extreme envelope of the to-be-separated signal, and calculates a mean envelope between the upper extreme envelope and the lower extreme envelope. The processing unit performs smoothing according to the smoothing parameters and the mean envelope to generate a smoothed mean envelope, and determines a trend component or a non-trend component according to the smoothed mean envelope.

Abstract: A method for evaluation of renal perfusion with power Doppler ultrasonography is disclosed in the present invention. Serial renal vascular images at different vascular areas including the whole vascular tree, interlobar, arcuate, and interlobular vessels were captured. Imaging processing software was designed to analyze the changes of power Doppler intensity of colored pixels within regions of interest (ROI). Power Doppler Vascularity index (PDVI) has been defined as the percentage of vascular perfusion within a region of interest (ROI). The renal vascular perfusion index (RVPI) is defined as the maximal power Doppler vascular index divided by minimal power Doppler vascular index (PDVImax/PDVImin) among the serial images. The mean of weighted power Doppler vascular index (WPDVImean) is defined as the average of the intensity of color pixels among the ROI within the serial images.

Abstract: A blood parameter measuring device and a method for measuring a blood parameter are provided. The blood parameter measuring device includes an emitted source, a receiver module, and an actuator. The emitted source is disposed at a side of a tissue to be analyzed and provides at least two different wavelengths of radiation. The receiver module is disposed at another side of the tissue to be analyzed to receive the attenuated radiation produced by the emitted source. The actuator is connected to at least one of the emitted source and the receiver module. The actuator generates a driving force to make the emitted source and the receiver module contacts the tissue to be analyzed, thereby imposing a normal stress on a surface of the tissue to be analyzed to change a wave path between the emitted source and the receiver module.

Abstract: A multi-dimensional empirical mode decomposition method is provided. The method can be applied in image texture analysis, such as medical image analysis. The method can adaptively decompose a three-dimensional image into a number of characteristic image layers and extract characteristic images showing more noticeable textures from the layers. The method uses the physical concept of field to perform the data mode decomposition to obtain envelope and tendency estimation of multi-dimensional data. The method can also be applied in time and frequency analysis of two-dimensional data or multi-channel data.

Abstract: An apparatus and a method for processing signal are provided. The signal processing apparatus comprises an input interface and a processing unit. The input interface receives smoothing parameters and a to-be-separated signal. The processing unit establishes an upper extreme envelope and a lower extreme envelope of the to-be-separated signal, and calculates a mean envelope between the upper extreme envelope and the lower extreme envelope. The processing unit performs smoothing according to the smoothing parameters and the mean envelope to generate a smoothed mean envelope, and determines a trend component or a non-trend component according to the smoothed mean envelope.

Abstract: An apparatus and a method for adaptive adaptive time-frequency analysis are suitable for nonlinear and nonstationary signal analyses. The method includes the following steps. A plurality of positions of local extrema of a signal is determined. Average frequencies between the local extrema and mean energy distribution corresponding thereto are estimated according to the positions of the local extrema of the signal. The estimated instantaneous energy distribution of the signal is determined by way of optimization according to each of the mean energy distribution between the local extrema. Finally, an instantaneous frequency of the signal is estimated according to the estimated instantaneous energy distribution of the signal.

Abstract: Disclosed is a method for detecting the degree of malignancy in tumors noninvasively, which comprises the steps of: using a Power Doppler ultrasound unit to scan a tumor and capture sequential color imagines in a complete heartbeat cycle, and choosing an area of interest (AREA_ROI) from the images; labeling pixels reflecting signals of bloodflow in the imagines during one heartbeat cycle to contour an area of tumor blood vessels (AREA_vessel); calculating a difference of PDVI between maximal systolic pressure and diastolic pressure during the heartbeat cycle to obtain tumor differential vascularity index (TDVI), in which PDVI is the ratio obtained by dividing pixels of AREA_vessel by a total area in the section of AREA_ROI; and determining the degree of malignancy by the TDVI. The method of the present invention can be applied to monitor the response of tumor to clinical treatment.

Abstract: A method for evaluation of renal perfusion with power Doppler ultrasonography is disclosed in the present invention. Serial renal vascular images at different vascular areas including the whole vascular tree, interlobar, arcuate, and interlobular vessels were captured. Imaging processing software was designed to analyze the changes of power Doppler intensity of colored pixels within regions of interest (ROI). Power Doppler Vascularity index (PDVI) has been defined as the percentage of vascular perfusion within a region of interest (ROI). The renal vascular perfusion index (RVPI) is defined as the maximal power Doppler vascular index divided by minimal power Doppler vascular index (PDVImax/PDVImin) among the serial images. The mean of weighted power Doppler vascular index (WPDVImean) is defined as the average of the intensity of color pixels among the ROI within the serial images.

Abstract: A signal processing method for performing hierarchical empirical mode decomposition (H-EMD) and an apparatus therefor are provided. In an embodiment, when empirical mode decomposition is performed on an input signal, an artificial assisting signal and the input signal are combined to assist the search for extrema and frequency reduction is performed in each iteration to eliminate the artificial assisting signal and make mode decomposition convergent so as to avoid mode mixing. In addition, in an embodiment, a hierarchical decomposition method is provided to decompose the input signal into a fewer number of fundamental modes. For needs in application, one of the fundamental modes can be further decomposed to produce a number of supplementary modes. In an embodiment, the H-EMD with appropriate frequency reduction can result in modes substantially independent of the form or the way of envelopes and can be applied to decompose multi-dimensional signals.

Abstract: A system and method thereof for capturing and reconstructing a dynamic 3D ultrasound image of a blood vessel are provided. The present system includes a ultrasound transducer, a motor positioning system, an electrocardiograph, a microprocessor for processing ultrasound images and signals capturing by the ultrasound transducer, and a monitor displaying the dynamic 3D ultrasound image. The motor positioning system controls the ultrasound transducer to capture 2D ultrasound images of the blood vessel at several locations in a predetermined urea. During the capturing process, capturing times, electrocardiograms and 3D locations of those captured 2D ultrasound images are simultaneously recoded. Finally, those captured 2D ultrasound images are reconstructed to the dynamic 3D ultrasound image of the blood vessel according to the time bases based on the phases of the electrocardiograms.

Abstract: A multi-dimensional empirical mode decomposition method is provided. The method can be applied in image texture analysis, such as medical image analysis. The method can adaptively decompose a three-dimensional image into a number of characteristic image layers and extract characteristic images showing more noticeable textures from the layers. The method uses the physical concept of field to perform the data mode decomposition to obtain envelope and tendency estimation of multi-dimensional data. The method can also be applied in time and frequency analysis of two-dimensional data or multi-channel data.

Abstract: Disclosed is a method for detecting the degree of malignancy in tumors noninvasively, which comprises the steps of: using a Power Doppler ultrasound unit to scan a tumor and capture sequential color imagines in a complete heartbeat cycle, and choosing an area of interest (AREA_ROI) from the images; labeling pixels reflecting signals of bloodflow in the imagines during one heartbeat cycle to contour an area of tumor blood vessels (AREA_vessel); calculating a difference of PDVI between maximal systolic pressure and diastolic pressure during the heartbeat cycle to obtain tumor differential vascularity index (TDVI), in which PDVI is the ratio obtained by dividing pixels of AREA_vessel by a total area in the section of AREA_ROI; and determining the degree of malignancy by the TDVI. The method of the present invention can be applied to monitor the response of tumor to clinical treatment.