An X-ray imaging system with multiple pulsed X-ray source tubes in motion to perform highly efficient and ultrafast 3D radiography is presented. There are multiple X-ray tubes from pulsed sources mounted on a structure in motion to form an array of X-ray tubes. The tubes move simultaneously relative to an object on a pre-defined arc track at a constant speed as a group. Each individual X-ray tube in each individual source can also move rapidly around its static position in a small distance. When a tube has a speed that is equal to group speed but with opposite moving direction, the tube and X-ray flat panel detector are activated through an external exposure control unit so that the tube stay momentarily standstill. It results in much reduced travel distance for each X-ray source tube and much lighter load for motion system. 3D X-ray scan can cover much wider sweeping angle in much shorter time and image analysis can also be done in real time.

An X-ray tomosynthesis imaging system using multiple pulsed X-ray source pairs in-motion to perform highly efficient and ultrafast 3D radiography is presented. Sources are mounted on a structure in motion to form pairs. The sources move simultaneously on a predefined arc trajectory at a constant speed as a group. In one pair, each individual source also moves rapidly around its static position in a small distance, but one moves in opposite direction to the other to cancel out momentum. When one source has a speed that is equal to group speed but with opposite direction, the source and X-ray detector are activated through an external exposure trigger. This allows the source to stay relatively standstill during activation. It results in much reduced travel distance for individual source. 3D data can be acquired with wider sweep angle in shorter time and image analysis is real-time. Heavy duty source can be used.

System and method are disclosed for imaging acquisition from sparse partial scans of distributed wide angle. During real time image reconstruction, artificial intelligence (AI) determines if there is enough information to perform diagnostics based on initial scans. If there is enough information from the fractional scans, then data acquisition stops; if more information is needed, then system performs another round of wide-angle sparse scans in a new location progressively until a result is satisfactory. The system reduces X-ray dose on a patient and performs quicker X-ray scan at multiple pulsed source-in-motion tomosynthesis imaging system. The method and system also significantly reduce the amount of time required to display high quality three-dimensional tomosynthesis images.

A system and method for improved image acquisition of multiple pulsed X-ray source-in-motion tomosynthesis imaging apparatus by generating the electrocardiogram (ECG) waveform data using an ECG device. Once a representative cardiac cycle is determined, system will acquire images only at rest period of heart beat. Real time ECG waveform is used as ECG synchronization for image improvement. The imaging apparatus avoids ECG peak pulse for better chest, lung and breast imaging under influence of cardiac periodical motion. As a result, smoother data acquisition, much higher data quality can be achieved. The multiple pulsed X-ray source-in-motion tomosynthesis machine is with distributed multiple X-ray sources that is spanned at wide scan angle. At rest period of one heartbeat, multiple X-ray exposures are acquired from X-ray sources at different angles. The machine itself has capability to acquire as many as 60 actual projection images within about two seconds.

The presented are X-ray diagnosis method and system using multiple pulsed X-ray source-in-motion tomosynthesis imaging technology. While taking X-ray instrument image data, artificial intelligence (AI) analyzes patient responses, compares current condition with the patient history and other patient information that may become part of a patient. It reports lesions location changes, sets severity threshold and warning status, generate treatment information. It also recommend to a X-ray region of interest (ROI) scan, a complete X-ray CT scan or other health care professionals and specialists.

A method of x-ray fluoroscopy images a region of interest at distinct first and second imaging projection angles using digital subtraction x-ray fluoroscopic imaging with a fiducial marker board positioned in a field of view containing the region of interest to produce first and second sets of images. Image segmentation information is determined to identify an anatomical feature in the region of interest imaged in the first set of images and the second set of images. The region of interest is then imaged using x-ray fluoroscopic imaging, again with the fiducial marker board positioned in a third field of view containing the region of interest, but without digital subtraction, to produce a third set of images. A virtual image of the anatomical feature is projected onto the third set of images, computed from the image segmentation information and from a predetermined geometric relationship of markers within the fiducial marker board.

A method for ascertaining pulmonary fibrosis disease progression or treatment response includes obtaining a first set of computed tomography (CT) images of a lung and determining a first Pulmonary Surface Index (PSI) score for the lung by detecting a first actual lung boundary of the lung within the first set of CT images, determining a first approximated lung boundary within the first set of CT images, and determining the PSI score using inputs based on the first actual lung boundary and the first approximated lung boundary. The method also includes obtaining a second set of CT images of the lung and determining a second PSI score for the lung using inputs based on a second actual lung boundary and a second approximated lung boundary. The method also includes assessing pulmonary fibrosis treatment response or disease progression based on the first PSI score and the second PSI score.

A method for implementing a dynamic three-dimensional lung map view for navigating a probe inside a patient's lungs includes loading a navigation plan into a navigation system, the navigation plan including a planned pathway shown in a 3D model generated from a plurality of CT images, inserting the probe into a patient's airways, registering a sensed location of the probe with the planned pathway, selecting a target in the navigation plan, presenting a view of the 3D model showing the planned pathway and indicating the sensed location of the probe, navigating the probe through the airways of the patient's lungs toward the target, iteratively adjusting the presented view of the 3D model showing the planned pathway based on the sensed location of the probe, and updating the presented view by removing at least a part of an object forming part of the 3D model.

A system and method for predicting a lung cancer risk based on a chest X-ray in which a nodule is detected in a chest of a patient based on an analysis of the chest X-ray using an image processing technique. A region of interest associated with the nodule is identified using the image processing technique. The region of interest is further analyzed using deep learning to determine a plurality of characteristics associated with the nodule. The plurality of characteristics comprises a size of the nodule, a calcification in the nodule, a homogeneity of the nodule and a spiculation of the nodule. Further, the plurality of characteristics is compared with a trained data model using deep learning. Based on the comparison, a risk score associated with the nodule is generated. Further, the lung cancer risk is predicted when the risk score exceeds a predefined threshold value.

A method for ascertaining pulmonary fibrosis disease progression or treatment response includes obtaining a first set of computed tomography (CT) images of a lung and determining a first Pulmonary Surface Index (PSI) score for the lung by detecting a first actual lung boundary of the lung within the first set of CT images, determining a first approximated lung boundary within the first set of CT images, and determining the PSI score using inputs based on the first actual lung boundary and the first approximated lung boundary. The method also includes obtaining a second set of CT images of the lung and determining a second PSI score for the lung using inputs based on a second actual lung boundary and a second approximated lung boundary. The method also includes assessing pulmonary fibrosis treatment response or disease progression based on the first PSI score and the second PSI score.