A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires image data including image data of a blood vessel of a subject. The processing circuitry performs analysis related to the blood vessel by using the image data, and specifies a region of interest in the blood vessel based on a result of the analysis. The processing circuitry performs fluid analysis on a region other than the region of interest at a first accuracy, and performs fluid analysis on the region of interest at a second accuracy that is higher than the first accuracy.

Methods for combining anatomical data and physiological data on a single image are provided. The methods include obtaining an image, for example, a raw near-infrared (NIR) image or a visible image, of a sample. The image of the sample includes anatomical structure of the sample. A physiologic map of blood flow and perfusion of the sample is obtained. The anatomical structure of the image and the physiologic map of the sample are combined into a single image of the sample. The single image of the sample displays anatomy and physiology of the sample in the single image in real time. Related systems and computer program products are also provided.

A network is machine trained to estimate flow by spatial location based on input of anatomy information. A medical scan of tissue may be used to generate flow information without the delay or difficulty of performing a medical scan configured for flow imaging or CFD. Anatomy imaging is used to provide flow estimates with the speed provided by the machine-learned network.

Some embodiments are directed to a method of estimating a velocity of a contrast agent. The method includes receiving a plurality of video frames that were produced using a dynamic contrast enhanced imaging process, each video frame including a plurality of pixels/voxels. Information from the video frames is used to estimate velocity vectors indicating the velocity and direction of the agent with the vascular networks. The estimated velocity can be used to diagnose cancer, such as prostate cancer. Instead of velocity vectors, agent trajectories can be determined also used for the same purpose.

Image processing methods and related systems (IPS) to process imagery (F) acquired during deposition of a substance at a region of interest, ROI The methods and systems allow visualizing in a graphics display (GD) various aspects of the deposited substance and/or determining, based on the imagery, the amount of said substance deposited at the ROI.

Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post-calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

A fuel injection pump for a diesel engine, including: a control rack arranged in a rack chamber formed between a pump head and a pump housing, and configured to adjust a fuel injection amount; a transmission shaft rotatably supported by a transmission shaft hole formed in the pump housing; and a lubricating oil passage formed in the pump housing, and configured to pressure-feed lubricating oil between the transmission shaft and the transmission shaft hole. The transmission shaft has an oil passage therein through which passage the lubricating oil pressure-fed to the lubricating oil passage partially passes, a first opening of the oil passage is communicated with the lubricating oil passage, and a second opening of the oil passage is formed on the outer circumferential surface of an upper portion of the transmission shaft, nearby the control rack.

Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient's anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.

A method for processing medical images includes analyzing a medical image to detect a medical condition from a list of medical conditions, wherein the list of medical conditions includes aortic dissection, pulmonary embolism, and coronary stenosis. Responsive to determining the medical image includes a first medical condition, the method generates a first report that includes information on a detection of the first medical condition. The method identifies, a medical specialist based on availability and medical expertise and sends to the identified medical specialist, the medical image and the first report for a decision on the detection of the first medical condition. Responsive to receiving the decision from the medical specialist, the method sends to a second electronic device, the decision, the medical image, and the first report.

A medical system (6000) includes an EIT module (30, 33, 8000), a ventilation module (7100), a dosing module (4), a data input module (50) and a control module (70). The control module (70) coordinates a breath-hold maneuver, which is carried out at the ventilation module (7100). The control module (70) coordinates a perfusion measurement and a data acquisition (50) of EIT data (3), which is carried out at the EIT module (30, 33, 8000). The control module (70) determines an indicator, which indicates a state of perfusion of the lungs, and makes this indicator of the state of perfusion of the lungs available.