A similar case retrieval apparatus includes: a lesion portion acquirer that acquires partial images including lesion portion images, an image feature extractor that extracts image features of each of the plurality of partial images; a location information acquirer that acquires location information of each of the partial images; a lateral position determiner that determines the right organ or the left organ in which each of the lesion portions exists based on the location information; a unilateral distribution identifier that determines whether or not a distribution of the lesion portions is a unilateral distribution; and a similar case retriever that retrieves case data from a case database including both case data for the unilateral distribution in the right organ and case data for the unilateral distribution in the left organ when the unilateral distribution identifier identifies that the distribution of the lesion portions is the unilateral distribution.

The disclosure relates to systems and methods for evaluating a blood vessel. The method includes receiving image data of the blood vessel acquired by an image acquisition device, and predicting, by a processor, blood vessel condition parameters of the blood vessel by applying a deep learning model to the acquired image data of the blood vessel. The deep learning model maps a sequence of image patches on the blood vessel to blood vessel condition parameters on the blood vessel, where in the mapping the entire sequence of image patches contribute to the blood vessel condition parameters. The method further includes providing the blood vessel condition parameters of the blood vessel for evaluating the blood vessel.

Presented herein are systems and methods that provide for improved computer aided display and analysis of nuclear medicine images. In particular, in certain embodiments, the systems and methods described herein provide improvements to several image processing steps used for automated analysis of bone scan images for assessing cancer status of a patient. For example, improved approaches for image segmentation, hotspot detection, automated classification of hotspots as representing metastases, and computation of risk indices such as bone scan index (BSI) values are provided.

Embodiments of the present disclosure include a method, device and computer readable medium involving receiving image data of one or more coronary arteries, generating a binary segmentation indicating presence of calcium in the one or more coronary arteries from the image data, generating a branch density of the one or more coronary arteries, and assigning a coronary artery label from the branch density to the binary segmentation such that at least one indication of presence of calcium of the binary segmentation is labeled as present in a specific one of the one or more coronary arteries.

A computer-implemented method and system of determining a material surface from a volumetric density file includes generating a density frequency distribution of a volumetric density file of a dental impression and determining an iso-value of density between air and a particular material in the density frequency distribution. A computer-implemented method and system of creating a digital model from a CT scan of a physical dental impression includes selecting an iso-value of density for a digital volumetric density file having one or more voxels, generating one or more digital surface points in virtual 3D space for each of one or more voxels, and selecting a subset of digital surface points from the one or more digital surface points. A computer-implemented method and system of optimizing a digital surface includes moving one or more digital surface points to satisfy a criteria of optimum digital surface selection.

System for treatment positioning is provided. The system may include a treatment component, an imaging component, and a couch. The treatment component may include a radiation source that has a radiation isocenter. The couch may be movable between the treatment component and the imaging component, and include a positioning line that has a positioning feature. The system may acquire at least one first image relating to a subject and the positioning line using the radiation source at a set-up position. The system may also acquire at least one second image relating to the subject and the positioning line using the imaging component at an imaging position. The system may further determine a treatment isocenter of a target of the subject based on the at least one second image, and determine a treatment position of the subject based on the first image(s), the second image(s), and the positioning line.

An analysis apparatus according to an embodiment includes an extraction unit, a calculation unit, and an evaluation unit. The extraction unit extracts a detection value in a tumor region, a blood region, and a muscle region from a nuclear medicine image of a subject administered with a drug containing a radiolabeled anticancer drug that works by accumulating in a tumor. The calculation unit calculates a first comparison value that is a comparison result between the detection value in the blood region and the detection value in the tumor region, and a second comparison value that is a comparison result between the detection value in the muscle region and the detection value in the tumor region. The evaluation unit evaluates an accumulation of the drug in the tumor, based on the first comparison value and the second comparison value calculated by the calculation unit.

Systems and methods for detecting aortic aneurysms using ensemble based deep learning techniques that utilize numerous computed tomography (CT) scans collected from numerous de-identified patients in a database. The system includes software that automates the analysis of a series of CT scans as input (in DICOM file format) and provides output in two dimensions: (1) ranking CT scans by risks of adverse events from aortic aneurysm, (2) providing aortic aneurysm size estimates. A repository of CT scans may be used for training of deep neural networks and additional data may be drawn from localized patient information from institutions and hospitals which grant permission.

A system and method is provided for processing a positron emission tomography (PET) image of a subject having received a dose of a radiotracer that serves as chemical analog of an MC-I inhibitor. Specifically, the processing may includes identifying portions of the at least one PET image that represent MC-I expression levels.

Systems, methods, and executable programs for providing lung candidacy information to health care professionals. A method includes receiving three-dimensional image data categorized as lung lobe voxels, airway voxels, or lung fissure voxels. A fissure integrity score is generated for the lung fissure voxels. First perspective transparent views of the categorized lung lobe voxels, the categorized airway voxels, and the categorized lung fissure voxels are generated based on a first point of view. The first perspective view of the lung fissure voxels includes a visual representation of fissure integrity based on the generated fissure integrity scores for the corresponding voxels. A report is generated that includes the generated views. The report is outputted.