Various embodiments are described herein for a system and associated method for performing collagen assessment of an object using Photoacoustic Image (PA) data obtained for the object, wherein the method is performed by a processing unit and the method comprises: obtaining beamformed PA image data for the object using at least three wavelengths related to chromophores including collagen, oxyhemoglobin and deoxyhemoglobin, the three wavelengths being less than 1000 nm; performing spectral decomposition on the beamformed PA image data using the three wavelengths to obtain data that is used for generating at least one collagen map; and determining a collagen score for the at least one collagen map.

The present disclosure relates to noninvasive methods for detecting liver fibrosis. Disclosed herein are noninvasive liver fibrosis detection methods that use Doppler Ultrasound devices and a physics-based machine learning method. Further disclosed herein are methods for detecting liver fibrosis in a subject by detecting and measuring the presence of a shift in the frequency of blood flow in the hepatic vein as compared to the frequency of blood flow in the portal vein.

An analysis apparatus includes processing circuitry configured to obtain quantitative values of a plurality of types of tissue properties relating to a region of interest of a subject, and generate a diagram of the region of interest based on the quantitative values.

Embodiments provide a deep learning framework to accurately segment liver and spleen using a convolutional neural network with both short and long residual connections to extract their radiomic and deep features from multiparametric MRI. Embodiments will provide an “ensemble” deep learning model to quantify biopsy derived liver fibrosis stage and percentage using the integration of multiparametric MRI radiomic and deep features, MRE data, as well as routinely available clinical data. Embodiments will provide a deep learning model to quantify MRE-derived liver stiffness using multiparametric MRI, radiomic and deep features and routinely-available clinical data.

The present invention relates to systems for use for radio frequency ablation. The systems can include one or more of an ablation tool, power source for use with the ablation tool and a backstop for use in conjunction with the ablation tool during surgical procedures. Preferred ablation tools comprise a series of three or more blade-shaped electrodes disposed in a linear, curved, curvilinear or circular array. The backstops are useful for reducing direct physical and thermal heat transfer injuries to the patient or surgeon during procedures using radiofrequency (RF) ablation devices.

The present invention relates to the generation of artificial IRM images of the liver. The invention also relates to a method, a system and a computer program product for generating MRI images of the liver.

Systems and methods are provided for quantifying and monitoring liver disease in a patient from voltage-time data. A method comprises receiving voltage-time data of a subject, the voltage-time data comprising voltage data of a plurality of leads of an electrocardiograph; generating a feature vector from the voltage-time data; providing the feature vector to a pretrained learning system; receiving from the pretrained learning system a status of liver disease in the subject.

The disclosure provides a modified EPI sequence for acquiring multi-shot and multi-echo images with interleaved blip-up and blip-down phase encoding; the blip-up and blip-down images are processed by topup in FSL to estimate the inhomogeneous main magnetic field B.sub.0 map that causes image distortions; the B.sub.0 map is then incorporated into the encoding matrix with a low rank constraint to form a joint reconstruction model; the joint reconstruction model is solved to obtain multiple distortion-free images; and the multiple distortion-free images are matched to dictionary to simultaneous acquire the quantitative T.sub.2 (=1/R.sub.2) and T.sub.2* (=1/R.sub.2*) maps. In the phantom and in-vivo measurements, the disclosed method rapidly acquires the comparable quantitative images within one hold-breath (for 20 s) to the conventional mapping method, thus providing important practical application value for evaluation of liver damage, iron level and cancer lesion.

An apparatus for non-invasive evaluations and in-vivo diagnostics includes an open magnet, an RF antenna, and an NMR analytics logical circuit communicatively coupled to the RF antenna, wherein the open magnet is shaped to generate a static magnetic field that extends unilaterally into an object or internal organ of a subject when the open magnet is positioned against or in proximity to the object or subject, the static and RF magnetic fields shaped to generate a sensitive volume within a target region. The RF antenna or antenna array is configured to transmit RF pulses into the target region of the object or internal organ and receive sets of NMR signals generated by hydrogen or other elements, and the NMR analytics logical circuit is configured to obtain and analyze sets of NMR signals.

The present disclosure relates to the generation of artificial MRI images of the liver. The disclosure also relates to a method, a system and a computer program product for generating MRI images of the liver without contract enhancement.