Industrial Technology Research Institute

National Taiwan University

Yio-Wha Shau

Sun-Hua Pao

Chun-Chuan Lin

Yu-Ching Chang

Tian-Yuan Chen

Shih-Bin Luo

Bai-Kuang Hwang

Arvin Huang-Te Li

Hsin-Hsiang Lo

Wan-Ting Tien

Chien-Lun Tseng

Tsung-Min Hsieh

Nai-Kuan Chou

De-Yi Chiou

Min Shih

Jeou-Jong Shyu

Tzu-Wen Tsai

Shuo-Meng Wang

Ming-Chien Yu

Chieh-Neng Young

Fon-Jou Hsieh

King-Jen Chang

Chiung-Nein Chen

Ma-Li Wang

Shih-Ying Chien

A medication concentration detecting device includes a medicine container, a three-way pipe, a light emitting member, a first light receiver and a processor. The medicine container has a chamber configured for accommodating nebulized medicine. The three-way pipe has a passageway connected to the chamber for the nebulized medicine to flow along the passageway. The light emitting member is disposed on the three-way pipe and configured for emitting a light beam toward the passageway. The first light receiver is disposed on the three-way pipe and configured for receiving the light beam and outputting a luminous flux signal. The processor is connected to the first light receiver and configured for calculating a luminous flux reference value according to the luminous flux signal. The luminous flux reference value is used for determining whether outputs a low nebulized medicine concentration warning.

Medication concentration detecting device for nebulizer

An intraocular pressure detecting device includes a pressure generation unit, a light source, an image sensing unit and a processing unit. The pressure generation unit applies pressure to a target surface of an eyeball along a first operation axis direction, such that a deformation is generated on the target surface. The light source emits light that irradiates the target surface along a second operation axis direction, so as to generate a speckle pattern on the target surface. The image sensing unit observes and records an image variation of the speckle pattern along a third operation axis direction. The processing unit is signally connected with the image sensing unit to receive an image of the speckle pattern. The processing unit identifies and analyzes a feature size of the image of the speckle pattern for obtaining an intraocular pressure value of the eyeball. An intraocular pressure detecting method is also described.

Intraocular pressure detecting device and detecting method thereof

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.

Apparatus and method for processing signal

A time domain signal analysis method is provided. The signal analysis method includes the following steps. A signal to be analyzed is received. The signal to be analyzed is iteratively sifted by using Empirical Mode Decomposition (EMD) to extract at least one intrinsic function (IMF). A normalized Hilbert transform is performed on the IMF. The transformed IMF includes phase information. The transformed IMF is processed by means of phase processing to obtain the processed IMF including angular frequency information. The foregoing signal analysis method could be utilized in an ultrasound imaging system to identify image information of ultrasound images.

Signal and image analysis method and ultrasound imaging system

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 (PDVI/PDVI) among the serial images. The mean of weighted power Doppler vascular index (WPDVI) is defined as the average of the intensity of color pixels among the ROI within the serial images. By using the RVPI and WPDVI, a more dynamic sense of vascular perfusion and a novel approach for the evaluation of renal vascular function in clinical practice can be provided.

Method for evaluation of renal vascular perfusion using power doppler ultrasonography

An image processing method is provided. The image processing method includes the following steps. A plurality of raw signal is received by a signal transceiving module of the ultrasound imaging system. It is determined whether each of the raw signals satisfies any condition in a condition group, and the raw signal satisfying any condition in the condition group is mapped to one of a plurality of preset constants to generate a plurality of first data. The raw signals not satisfying any condition in the condition group are processed according to a calculation formula to generate a plurality of second data. A beamforming procedure is simultaneously performed on the first and second data to obtain a beamformed image. The beamformed image is transformed to obtain an image of a region to be detected. Furthermore, an imaging system using the foregoing image processing method is also provided.

Imaging system and image processing method thereof

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.

Multi-dimensional empirical mode decomposition (EMD) method for image texture analysis

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.

Quantitative non-invasive method for detecting degree of malignancy in tumors and application thereof

A method and apparatus for keyboard instrument learning are disclosed. The learning device comprises: a data access/storage device, for storing musical compositions and fingerings; an image signal output device for outputting image signals; a processing unit; and an imaging unit, capable of capturing an image of fingers fitted with marking units in respective and an image of surface where the fingers are placed. When the fingers fitted with the marking units are placed on an actual keyboard, the processing unit is enabled to compare the i,age captured by the imaging unit with a musical composition program so as to generate a control signal accordingly while using the control signal to issue an output signal. In another embodiment, when the fingers fitted with the marking units are placed on the surface without actual keyboard, the output unit issues an output signal with virtual keyboard for directing a user to press keys of the virtual keyboard indicated by the output signal while enabling the processing unit to identify whether the correct keys are passed and further are pressed by the correct fingers.

Method and apparatus for keyboard instrument learning

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Taipei, Taiwan

Yio-Wha Shau