Abstract: A method for predicting clinical severity of a neurological disorder includes steps of: a) identifying, according to a magnetic resonance imaging (MRI) image of a brain, brain image regions each of which contains a respective portion of diffusion index values of a diffusion index, which results from image processing performed on the MRI image; b) for one of the brain image regions, calculating a characteristic parameter based on the respective portion of the diffusion index values; and c) calculating a severity score that represents the clinical severity of the neurological disorder of the brain based on the characteristic parameter of the one of the brain image regions via a prediction model associated with the neurological disorder.

Abstract: The method for detecting mechanical and magnetic features comprises the steps of: aiming a probe of the sensor at a sample; defining several detected points for detection on the sample; detecting one of points and comprising the steps of: approaching the probe to the detected point from a predetermined height; contacting the probe with the detected point and applying a predetermined force on the detected point; making the probe far away from the detected point until to the predetermined height; shifting the probe to the next point for detection and repeating the detection; collecting the data of each of the detected points while the probe rapidly approaches to the points from the predetermined height; using a signal decomposition algorithm to transform the collected data to a plurality of data groups; and choosing a part of the data groups to be as data of feature distributions of the sample.

Abstract: The method for detecting mechanical and magnetic features comprises the steps of: aiming a probe of the sensor at a sample; defining several detected points for detection on the sample; detecting one of points and comprising the steps of: approaching the probe to the detected point from a predetermined height; contacting the probe with the detected point and applying a predetermined force on the detected point; making the probe far away from the detected point until to the predetermined height; shifting the probe to the next point for detection and repeating the detection; collecting the data of each of the detected points while the probe rapidly approaches to the points from the predetermined height; using a signal decomposition algorithm to transform the collected data to a plurality of data groups; and choosing a part of the data groups to be as data of feature distributions of the sample.

Abstract: Disclosed herein is a method for diagnosing a neurological disorder based on at least one magnetic resonance imaging (MRI) image. The method includes identifying brain image regions that contain a respective portion of diffusion index values of at least one diffusion index. For each of the brain image regions, a characteristic parameter based on the respective portion of the diffusion index values is calculated. a diagnoses is then made for the brain using one of predetermined categories of the neurological disorder by performing classification on a combination of the characteristic parameters via a classifier.

Abstract: A method is to be implemented by a computing device and includes steps of: a) identifying, according to a magnetic resonance imaging (MRI) image, brain image regions each of which contains a respective portion of diffusion index values of at least one diffusion index, which results from image processing performed on said at least one MRI image; b) for each of the brain image regions, calculating a characteristic parameter based on the respective portion of the diffusion index values; and c) diagnosing the brain examined with one of predetermined categories of the neurological disorder by performing classification on a combination of the characteristic parameters via a classifier.

Abstract: A method for predicting clinical severity of a neurological disorder includes steps of: a) identifying, according to a magnetic resonance imaging (MRI) image of a brain, brain image regions each of which contains a respective portion of diffusion index values of a diffusion index, which results from image processing performed on the MRI image; b) for one of the brain image regions, calculating a characteristic parameter based on the respective portion of the diffusion index values; and c) calculating a severity score that represents the clinical severity of the neurological disorder of the brain based on the characteristic parameter of the one of the brain image regions via a prediction model associated with the neurological disorder.

Abstract: The invention relates to the use of diffusion kurtosis imaging (DKI) in the diagnosis of Parkinson Disease related neurodegenerative disorders, including (but not limited to) Parkinson's disease (PD) and Parkinson plus syndromes.

Abstract: The invention relates to the use of diffusion kurtosis imaging (DKI) in the diagnosis of Parkinson Disease related neurodegenerative disorders, including (but not limited to) Parkinson's disease (PD) and Parkinson plus syndromes.

Abstract: A charge pump circuit includes at least one stage between an input end and an output end. The at least one stage includes a first CMOS transistor coupled with a first capacitor and a second CMOS transistor coupled with a second capacitor. The at least one stage is capable of receiving a first timing signal and a second timing signal for pumping an input voltage at the input end to an output voltage at the output end. During a transitional period of the first timing signal and the second timing signal, the at least one stage is capable of substantially turning off at least one of the first CMOS transistor and the second CMOS transistor for substantially reducing leakage currents flowing through at least one of the first CMOS transistor and the second CMOS transistor.

Abstract: A charge pump circuit includes at least one stage between an input end and an output end. The at least one stage includes a first CMOS transistor coupled with a first capacitor and a second CMOS transistor coupled with a second capacitor. The at least one stage is capable of receiving a first timing signal and a second timing signal for pumping an input voltage at the input end to an output voltage at the output end. During a transitional period of the first timing signal and the second timing signal, the at least one stage is capable of substantially turning off at least one of the first CMOS transistor and the second CMOS transistor for substantially reducing leakage currents flowing through at least one of the first CMOS transistor and the second CMOS transistor.

Abstract: A charge pump circuit includes at least one stage between an input end and an output end. The at least one stage includes a first CMOS transistor coupled with a first capacitor and a second CMOS transistor coupled with a second capacitor. The at least one stage is capable of receiving a first timing signal and a second timing signal for pumping an input voltage at the input end to an output voltage at the output end. During a transitional period of the first timing signal and the second timing signal, the at least one stage is capable of substantially turning off at least one of the first CMOS transistor and the second CMOS transistor for substantially reducing leakage currents flowing through at least one of the first CMOS transistor and the second CMOS transistor.

Abstract: A charge pump circuit includes at least one stage between an input end and an output end. The at least one stage includes a first CMOS transistor coupled with a first capacitor and a second CMOS transistor coupled with a second capacitor. The at least one stage is capable of receiving a first timing signal and a second timing signal for pumping an input voltage at the input end to an output voltage at the output end. During a transitional period of the first timing signal and the second timing signal, the at least one stage is capable of substantially turning off at least one of the first CMOS transistor and the second CMOS transistor for substantially reducing leakage currents flowing through at least one of the first CMOS transistor and the second CMOS transistor.