An evaluation method of a spheroid comprises specifying a spheroid region taken up by the spheroid out of the image including the spheroid and a surrounding region thereof, obtaining an average value of an optical density of the spheroid and a magnitude of a variation of the optical density in the spheroid from an image density of the spheroid region, obtaining a circularity of the spheroid from a contour of the spheroid region, obtaining a sharpness of the spheroid from the image densities of the spheroid and the surrounding region thereof, and obtaining the collapse degree of the spheroid by substituting the average value of the optical density, the magnitude of the variation of the optical density, the circularity and the sharpness into a predetermined operational expression.

An evaluation method of a spheroid comprises specifying a spheroid region taken up by the spheroid out of the image including the spheroid and a surrounding region thereof, obtaining an average value of an optical density of the spheroid and a magnitude of a variation of the optical density in the spheroid from an image density of the spheroid region, obtaining a circularity of the spheroid from a contour of the spheroid region, obtaining a sharpness of the spheroid from the image densities of the spheroid and the surrounding region thereof, and obtaining the collapse degree of the spheroid by substituting the average value of the optical density, the magnitude of the variation of the optical density, the circularity and the sharpness into a predetermined operational expression.

A system includes a processor circuit in communication with an intraluminal imaging device. The processor circuit is configured to receive an intraluminal image obtained by the intraluminal imaging device while the intraluminal imaging device is positioned within a body lumen of a patient. The processor circuit also receive a user input selecting one location within the intraluminal image and another user input selecting another location within the intraluminal image. These two locations within the intraluminal image define boundaries of a sector of the intraluminal image associated with a tissue type. The processor circuit determines an angle of the sector defined by the two locations. The intraluminal image and a visual representation of the angle are displayed on a screen display.

A system includes a processor circuit in communication with an intraluminal imaging device. The processor circuit is configured to receive an intraluminal image obtained by the intraluminal imaging device while the intraluminal imaging device is positioned within a body lumen of a patient. The processor circuit also receive a user input selecting one location within the intraluminal image and another user input selecting another location within the intraluminal image. These two locations within the intraluminal image define boundaries of a sector of the intraluminal image associated with a tissue type. The processor circuit determines an angle of the sector defined by the two locations. The intraluminal image and a visual representation of the angle are displayed on a screen display.

A medical image processing apparatus of an embodiment includes processing circuitry. The processing circuitry acquires a medical image of a lung field of a patient, identifies anatomical regions constituting the thorax of the patient based on the medical image, estimates a respiratory state when the medical image has been captured based on the anatomical regions, and executes processing based on the respiratory state.

A medical image processing apparatus of an embodiment includes processing circuitry. The processing circuitry acquires a medical image of a lung field of a patient, identifies anatomical regions constituting the thorax of the patient based on the medical image, estimates a respiratory state when the medical image has been captured based on the anatomical regions, and executes processing based on the respiratory state.

A method for verifying a feature of a mask design. The method includes determining localized shapes of the feature, and determining whether there is a breach by the feature of verification criteria based on the localized shapes. The verification criteria specifies correspondence between a threshold of a pattern characteristic and a localized shape. For example, the feature of the mask design may be a freeform curvilinear mask feature. The localized shapes may include local curvatures of individual locations on segments of the feature. In some embodiments, the threshold of the pattern characteristic is a spacing threshold, and the verification criteria specifies the spacing threshold as a function of the local curvatures. The method may facilitate enhanced mask rules checks (MRC), including better definition and verification of MRC criteria for freeform curvilinear masks, and/or have other advantages.

A print control apparatus is configured to transfer transparent protective ink onto an image printed on a substrate. The print control apparatus includes an extraction unit configured to extract a contour of a subject in the image, and a control unit configured to generate print data for transferring the protective ink using a printing apparatus, based on the extracted contour of the subject. The control unit generates the print data by assigning a high gradation value to a contour line corresponding to the extracted contour of the subject, assigning a low gradation value to a region corresponding to the subject, and assigning a mixture of the high gradation value and the low gradation value to an outer peripheral region of the subject.

A print control apparatus is configured to transfer transparent protective ink onto an image printed on a substrate. The print control apparatus includes an extraction unit configured to extract a contour of a subject in the image, and a control unit configured to generate print data for transferring the protective ink using a printing apparatus, based on the extracted contour of the subject. The control unit generates the print data by assigning a high gradation value to a contour line corresponding to the extracted contour of the subject, assigning a low gradation value to a region corresponding to the subject, and assigning a mixture of the high gradation value and the low gradation value to an outer peripheral region of the subject.

Generating a correction algorithm includes obtaining a model of an eye, the model including a front portion with optics to mimic a cornea and a lens of a human eye, and a rear portion having a generally hemispherical-shaped body to mimic a retina of the human eye. The rear portion includes physical reference lines on an inside surface of the generally hemispherical-shaped body. Images of the model are captured using an image capturing device aimed at the model. Vertices of the physical reference lines are identified according to a given projection technique for displaying generally hemispherical-shaped body in a two-dimensional image in the captured images. Idealized placement of the vertices of the physical reference lines is obtained according to the given projection technique. The result is a correction algorithm used to adjust any pixel of an image of an actual eye in the x-axis and in the y-axis.