Systems and methods are provided for determine the fat composition in an organ of interest using a non-invasive health measurement system. The non-invasive health measurement system may include an open magnet NMR apparatus. The NMR apparatus may measure NMR signals in a sensitive volume of a patient. The sensitive volume may coincide with an organ of interest, such as a liver. Systems and methods disclosed herein may provide for separation of the water contribution and the fat contribution to the measured NMR signal. Diffusion based separation, T.sub.2 based separation, and T.sub.1 based separation may each serve as different methods for separating the water and fat contributions to the signal. Separating the water and fat contributions to the single may allow for computation of a proton density fat fraction which may reflect the fat composition of the organ of interest.

Disclosed are systems and methods utilizing an infrared probe and discriminating software to rapidly discriminate abnormal tissue processes from normal tissue during surgery, physical examination of in-situ lesions, and in the assessment of biopsy and resected tissue specimens. Examples demonstrate discrimination of cancerous from noncancerous tissues. The discriminating software, i.e. the metrics, algorithms, calibrant spectra, and decision equations, allows tissue to be identified as abnormal or normal using a minimum of infrared (IR) wavelengths in order to be measured rapidly. The probe records IR metrics approximately 1000 times faster than current commercial instruments, i.e. on a timescale fast enough for clinical use. The probe uses a tunable mid-infrared laser with a small set of selected wavelengths that are optimized for detecting the chemical and molecular signatures of tissue specific lesions to include, but not limited to, cancer, preneoplasia, intracellular accumulations (e.g. steatosis), inflammation, and wound healing.

A quantitative, ultrashort time to echo, contrast-enhanced magnetic resonance imaging technique is provided. The technique can be used to accurately measure contrast agent concentration in the blood, to provide clear, high-definition angiograms, and to measure absolute quantities of cerebral blood volume on a voxel-by-voxel basis.

The invention relates to a system for assessing decompensated cirrhosis (10). characterised by comprising: at least one patient application module configured to be connected to at least one sensor device (S) and/or at least one wearable device (W. B) to collect first patient data therefrom, and/or configured to receive a manual input of second patent data and/or configured to assess higher mental functions of a patient as third patient data: at least one practitioner application module configured to receive the first patient data and/or the second patient data and/or third patient data, and process the said patient data to detect signs related to decompensated cirrhosis complications. The invention further relates to a kit and a computer implemented method based on that system (10).

The invention relates to liver diseases. Liver diseases notably encompass chronic liver disease and liver cancer (a liver primitive cancer or metastasis). There is therefore a need to be able to extract biomarkers for subjects to suffer from this disease. As a consequence, the inventors worked on a method for post-processing images of a region of interest to obtain at least one perfusion parameter and at least one transport parameter. Such method enables to obtain a method which can be implemented on computer and provides access to relevant parameters for liver diseases in an easier and more accurate way. This method may be applied for predicting that a subject is at risk of suffering from such disease, diagnosing a disease, identifying a therapeutic or a biomarker and screening compounds useful as a medicine.

An automatic classification method for distinguishing between indolent and clinically significant carcinoma using multiparametric MRI (mp-MRI) imaging is provided. By utilizing a convolutional neural network (CNN), which automatically extracts deep features, the hierarchical classification framework avoids deficiencies in current schemes in the art such as the need to provide handcrafted features predefined by a domain expert and the precise delineation of lesion boundaries by a human or computerized algorithm. This hierarchical classification framework is trained using previously acquired mp-MRI data with known cancer classification characteristics and the framework is applied to mp-MRI images of new patients to provide identification and computerized cancer classification results of a suspicious lesion.

A system and method for calculating a flip angle schedule is provided. The technique includes selecting an initial condition, providing a function for calculating flip angles, calculating flip angles, assessing the flip angles, and repeating the calculation of the flip angles by adjusting the function until a desired flip angle schedule is obtained.

Methods and systems for diagnosis, prognosis and monitoring of hepatocellular carcinoma (HCC). Specifically, the present invention relates to the use of breath tests based on isotope-labeled octanoate in the detection and monitoring of HCC.

This method for qualitatively evaluating human livers comprises: a step (301) of computing normalized histograms of colour channels from a portion of a photograph of a liver; a step (304) of loading coefficients obtained at the end of a training phase; a step (305) of extracting from the histograms values corresponding to variables retained at the end of the training phase; a step (306) of computing a linear combination of the extracted values weighted with the loaded coefficients; and a step (308, 309) of displaying information representative of the result of the computation of the linear combination.

A computer-implemented method for liver health assessment, comprising: receiving EIT data associated with a liver of a subject; and processing the EIT data to determine a health condition of the liver of the subject.