According to some aspects, an image processing apparatus is provided. The image processing apparatus includes circuitry configured to receive at least two images of a biological sample and determine motion information for a plurality of regions of the at least two images. The motion information corresponds to motion of the biological sample. The circuitry is further configured to generate a graphical representation of at least two characteristic amounts. The at least two characteristic amounts correspond to a region of the plurality of regions and one characteristic amount of the at least two characteristic amounts is indicative of the motion information.

An information processing apparatus includes a hardware processor. The hardware processor obtains an abnormal shadow candidate detection result generated based on a medical image obtained by a medical image generation apparatus. Based on the obtained abnormal shadow candidate detection result, the hardware processor determines the number of image interpreters who interpret the medical image. The hardware processor outputs the determined number of image interpreters.

Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

A non-transitory computer-readable recording medium storing an image interpretation support program that causes a computer to execute a process, the process including generating first data indicating a first internal structure of a predetermined object, based on a first cross-sectional image group acquired with respect to the predetermined object; detecting a structural change of the first internal structure from a second internal structure of the predetermined object, based on second data indicating the second internal structure and the generated first data, the second data being generated based on a second cross-sectional image group acquired at a past time; identifying a new cross-section with respect to the predetermined object based on the structural change; generating a cross-sectional image of the predetermined object with respect to the new cross-section, based on the first cross-sectional image group; and displaying the generated cross-sectional image together with first information indicating the detected structural change.

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.

According to some aspects, an image processing apparatus is provided. The image processing apparatus includes circuitry configured to receive at least two images of a biological sample and determine motion information for a plurality of regions of the at least two images. The motion information corresponds to motion of the biological sample. The circuitry is further configured to generate a graphical representation of at least two characteristic amounts. The at least two characteristic amounts correspond to a region of the plurality of regions and one characteristic amount of the at least two characteristic amounts is indicative of the motion information.

An information processing apparatus includes an acquisition unit that acquires, in a medical image, a first region and a second region different from the first region, a limiting unit that limits extracting a third region, connecting the first region and the second region, within a range including an extraction direction determined based on the first region; and an extraction unit that extracts the third region within the range limited by the limiting unit.

One embodiment include an image acquisition circuit that accesses a pre-treatment and a post-treatment image of a region of tissue demonstrating non-small cell lung cancer (NSCLC), a segmentation and registration circuit that annotates the tumor represented in the images, and that registers the pre-treatment image with the post-treatment image; a feature extraction circuit that selects a set of pre-treatment and a set of post-treatment radiomic features from the registered image; a delta radiomics circuit that generates a set of delta radiomic features by computing a difference between the set of post-treatment radiomic features and the set of pre-treatment radiomic features; and a classification circuit that generates a probability that the region of tissue will respond to immunotherapy based on the difference, and that classifies the region of tissue as a responder or non-responder. Embodiments may generate an immunotherapy treatment plan based, at least in part, on the classification.

A method of extending a segmentation of an image using navigated image data from a navigation system includes tracking, with the navigation system, at least one of a traveled path and a position of an imaging device relative to an initial segmentation of 3D image data including an initial treelike structure. Navigated image data including image data including at least one 2D or 3D image is captured with the imaging device. A point from the navigated image data corresponding to a potential airway structure is obtained by the navigation system. The initial segmentation of 3D image data is extended by the navigation system using the point obtained from the navigated image data.

Disclosed are a method and a device for detecting pulmonary nodule in Computed Tomography (CT) image, as well as a computer-readable storage medium. The method for detecting pulmonary nodule in CT image includes: obtaining a CT image to be detected, performing a pixel segmentation processing on the CT image through a pre-stored three-dimensional convolutional neural pixel segmentation network, to obtain a probability graph corresponding to the CT image, and obtaining a candidate nodule region by marking a connected domain on the probability graph; and predicting the candidate nodule region by various pre-stored prediction models corresponding to different three-dimensional convolutional neural network classifiers, to obtain various probability prediction values of the candidate nodule region, and comprehensively processing the various probability prediction values to obtain a classification result of the candidate nodule region.