A method for evaluating image quality is provided. The method may include: obtaining an image, the image including a plurality of elements, each element of the plurality of elements being a pixel or voxel, each element having a gray level; determining, based on a maximum gray level of the plurality of elements, one or more thresholds for segmenting the image; determining one or more sub-images of a region of interest by segmenting, based on the one or more thresholds, the image; and determining, based on the one or more sub-images of the region of interest, a quality index for the image.

Multimodal imaging apparatus and methods include a rotatable gantry system with multiple sources of radiation comprising different energy levels (for example, kV and MV). Fast slip-ring technology and helical scans allow data from multiple sources of radiation to be combined or utilized to generate improved images and workflows, including for IGRT. Features include large field-of-view (LFOV) MV imaging, kV region-of-interest (ROI) imaging, and scalable field-of-view (SFOV) dual energy imaging.

The present disclosure provides a reconstruction method for motion compensated high quality four-dimensional (4D)-Cone Beam Computed Tomography (CBCT) image based on bilateral filtering, including the following steps: step 1, building a motion compensated three-dimensional (3D)-CBCT reconstruction model based on a simultaneous algebraic reconstruction technique (SART) to reconstruct a high quality CBCT image of a reference phase (phase 0%); step 2, creating an iterative optimization procedure and estimating a 4D Deformable Vector Field (DVF) model between phase 0% and other 4D phase images, thereby obtaining an exact 4D-DVF inclusive of an inverse sliding motion on a surface of a locomotive organ; and step 3, successively deforming the high quality phase 0% image in accordance with an optimized 4D-DVF to obtain a sequence of final high quality 4D-CBCT images. This method permits exact reconstruction of high quality 4D-CBCT images without changing the hardware structure of an existing linear accelerator for conventional radiotherapy.

A radiotherapy delivery device is provided. The device includes a source of therapeutic radiation and a first detector positioned to receive radiation from the source of therapeutic radiation. The device also includes a source of imaging radiation and a second detector positioned to receive radiation from the source of imaging radiation. A collimator assembly is positioned relative to the second source of radiation to selectively control a shape of a radiation beam emitted by the second radiation source to selectively expose part or the whole of the second radiation detector. A reconstruction processor can be operatively coupled to the detector and configured to generate patient images based on radiation received by the second detector from the second source of radiation. The device is configured to move from one imaging geometry to another using all or part of the second detector.

In various embodiments, the present invention provides an improved system and method for motion estimation and motion compensation in cone beam computer tomography (CBCT). The present invention utilizes a method for alternating minimization between volume and motion sub-iterations and results in an improved system and method for motion estimation and compensation in CBCT.

The present disclosure is related to systems and methods for motion signal recalibration. The method includes obtaining a motion signal of a subject based on positron emission tomography (PET) data of the subject. The motion signal may represent a plurality of motion cycles. The method includes determining a distribution of the motion cycles. The distribution of the motion cycles may indicate a probability that each motion cycle of the plurality of motion cycles corresponds to an actual motion cycle. The method includes correcting the motion cycles of the motion signal based on the distribution of the motion cycles to obtain corrected motion cycles. The method includes reconstructing a PET image by gating the PET data based on the corrected motion cycles.

Disclosed are image recognition Artificial Intelligence (AI) training methods for multiple pulsed X-ray source-in-motion tomosynthesis imaging system. Image recognition AI training can be performed three ways: first, using existing acquired chest CT data set with known nodules to generate synthetic tomosynthesis Images, no X-ray radiation applied; second, taking X-ray raw images with anthropomorphic chest phantoms with simulated lung nodules, applying X-ray beam on phantom only; third, acquiring X-ray images using multiple pulsed source-in-motion tomosynthesis images from real patients with real known nodules and without nodules. An X-ray image recognition training network that is configured to receive X-ray training images, automatically determine whether the received images indicate a nodule or lesion condition. After training, image knowledge is updated and stored at knowledge database.

An X-ray imaging system using multiple pulsed X-ray source pairs in-motion to perform highly efficient and ultrafast 3D radiography is presented. The sources move simultaneously on arc trajectory at a constant speed as a group. 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 linear momentum. Trajectory can also be arranged at a ring structure horizontally. In X-ray source pairs each moves in opposite angular direction to another to cancel out angular momentum. When an individual X-ray source has a speed that equals to group speed but an opposite linear or angular direction, the individual X-ray source is triggered through an external exposure control unit. This allows the source to stay relatively standstill during activation. 3D data can be acquired with wider view in shorter time and image analysis is real-time.

An X-ray imaging system using multiple pulsed X-ray sources to perform highly efficient and ultrafast 3D radiography is presented. There are multiple pulsed X-ray sources mounted on a structure in motion to form an array of sources. The multiple X-ray sources move simultaneously relative to an object on a pre-defined arc track at a constant speed as a group. Electron beam inside each individual X-ray tube is deflected by magnetic or electrical field to move focal spot a small distance. When focal spot of an X-ray tube beam has a speed that is equal to group speed but with opposite moving direction, the X-ray source and X-ray flat panel detector are activated through an external exposure control unit so that source tube stay momentarily standstill equivalently. 3D scan can cover much wider sweep angle in much shorter time and image analysis can also be done in real-time.

An X-ray imaging system using multiple pulsed X-ray sources in motion to perform high efficient and ultrafast 3D radiography using an X-ray flexible curved panel detector is presented. There are multiple pulsed X-ray sources mounted on a structure in motion to form an array of sources. The sources move simultaneously relative to an object on a predefined arc track at a constant speed as a group. Each individual X-ray source can move around its static position at a small distance. When an individual source has a speed equal to group speed, but with opposite moving direction, the individual source and detector are activated. This allows source to stay relatively standstill during activation. The operation results in reduced source travel distance for each individual source. 3D radiography image data can be acquired with much wider sweep angle in much shorter time, and image analysis can also be done in real-time.