Abstract: A MRS (magnetic resonance spectroscopy or nuclear magnetic resonance NMR)-based PTSD (post-traumatic stress disorder) and mTBI (mild traumatic brain injury) diagnostic system and method uses MRS signals, already pre-processed by the MRS scanner software. The signals are collected in vivo from specific regions of the brain. A wavelet decomposition is applied to the MRS signals, and the amplitude of the wavelet coefficients and their location in the MRS signals are used as features for training diagnostic classifiers of disease states. These classifiers are identified through analysis of features of individuals whose health status is known. Once the classifiers are trained, patients can be diagnosed by using the same wavelet features extracted from in vivo MRS scans of their brain regions.

Abstract: A method and a system for analysis of raw MRS data, in the form of signal strength versus chemical shift (ppm), from multiple scanners, includes “signal estimation” from each raw data set, followed by cross-scanner “data harmonization” of results. The final resulting MRS signals are consistent from one scanner to another, and are used for analysis by radiologists and other physicians.

Abstract: A method and a system for analysis of raw MRS data, in the form of signal strength versus chemical shift (ppm), from multiple scanners, includes “signal estimation” from each raw data set, followed by cross-scanner “data harmonization” of results. The final resulting MRS signals are consistent from one scanner to another, and are used for analysis by radiologists and other physicians.

Abstract: A 2-D MRS (magnetic resonance spectroscopy), or equivalently, NMR (nuclear magnetic resonance), pre-processing method produces clean MRS signals from raw data for possible use, among other applications, for diagnoses of neurological disorders such as PTSD and mTBI of the brain. The specific 2-D MRS data referred to in this invention are the 2-D MRS Correlation Spectroscopy or 2-D COSY data.

Abstract: A MRS (magnetic resonance spectroscopy or nuclear magnetic resonance NMR)-based PTSD (post-traumatic stress disorder) and mTBI (mild traumatic brain injury) diagnostic system and method uses MRS signals, already pre-processed by the MRS scanner software. The signals are collected in vivo from specific regions of the brain. A wavelet decomposition is applied to the MRS signals, and the amplitude of the wavelet coefficients and their location in the MRS signals are used as features for training diagnostic classifiers of disease states. These classifiers are identified through analysis of features of individuals whose health status is known. Once the classifiers are trained, patients can be diagnosed by using the same wavelet features extracted from in vivo MRS scans of their brain regions.

Abstract: The present disclosure describes a system and method to classify optical coherence tomography (OCT) images. The present system can classify OCT images without first segmenting the retina tissue. The system can generate one or more profiles from vertical transects through the OCT images. The system can identify image statistics based on the one or more profiles. The system's classifier can then classify the OCT images based on the identified image statistics.

Abstract: The present disclosure describes a system and method to classify optical coherence tomography (OCT) images. The present system can classify OCT images without first segmenting the retina tissue. The system can generate one or more profiles from vertical transects through the OCT images. The system can identify image statistics based on the one or more profiles. The system's classifier can then classify the OCT images based on the identified image statistics.

Abstract: This disclosure provides systems, methods, and apparatus for analyzing a video are disclosed. An input video signal can be received and a quality metric associated with the input video signal can be determined. A parameter to be used in a first object tracking process can be selected, based in part on the quality metric associated with the input video signal. A background model can be extracted from the input video signal based on an online median estimate of the intensity values of the pixels in the image frames. The online median estimate can be calculated using a quantile function.

Abstract: This disclosure provides systems, methods, and apparatus for analyzing a video are disclosed. An input video signal can be received and a quality metric associated with the input video signal can be determined. A parameter to be used in a first object tracking process can be selected, based in part on the quality metric associated with the input video signal. A background model can be extracted from the input video signal based on an online median estimate of the intensity values of the pixels in the image frames. The online median estimate can be calculated using a quantile function.

Abstract: Methods involving extraction of information from the inherent variability of physiometrics, including data on cardiovascular and pulmonary functions such as heart rate variability, characteristics of ECG traces, pulse, oxygenation of subcutaneous blood, respiration rate, temperature or CO2 content of exhaled air, heart sounds, and body resonance, can be used to identify individual subjects, particularly humans. Biometric data for use in the methods can be obtained either from contact sensors or at a distance. The methods can be performed alone or can be fused with previous identification algorithms.

Abstract: Methods involving extraction of information from the inherent variability of physiometrics, including data on cardiovascular and pulmonary functions such as heart rate variability, characteristics of ECG traces, pulse, oxygenation of subcutaneous blood, respiration rate, temperature or CO2 content of exhaled air, heart sounds, and body resonance, can be used to identify individual subjects, particularly humans. Biometric data for use in the methods can be obtained either from contact sensors or at a distance. The methods can be performed alone or can be fused with previous identification algorithms.