Abstract: In a medical image processing apparatus, a medical image processing method, and a medical image processing program, in a case where there are a plurality of past brain images, it is possible to select a past brain image with which the atrophy rate of the brain can be accurately calculated. An image acquisition unit acquires a target brain image Bt as a diagnostic target and a plurality of past brain images Bpi, which have earlier imaging dates and times than the target brain image Bt, for the same subject. A similarity calculation unit calculates the similarity between each of the plurality of past brain images Bpi and a standard brain image Bs. A selection unit selects a reference brain image B0 serving as a reference for calculating the amount of change of the brain from the plurality of past brain images Bpi.

Abstract: The medical information display apparatus includes an image acquisition unit that acquires a first brain image which is a brain image of a subject captured at a first time point and a second brain image captured at a second time point later in time than the first time point, a registration unit that performs registration between the first and the second brain image, an image analysis unit that extracts a first cavity region and a second cavity region from the first brain image and the second brain image, respectively, a display unit, and a display controller displays, a cavity expansion part included in a first non-cavity region, which is a region other than the first cavity region, and included in the second cavity region in a distinguishable manner from a region other than the cavity expansion part from a result of the registration between the first and second brain image.

Abstract: In a medical image processing apparatus, a medical image processing method, and a medical image processing program, in a case where there are a plurality of past brain images, it is possible to select a past brain image with which the atrophy rate of the brain can be accurately calculated. An image acquisition unit acquires a target brain image Bt as a diagnostic target and a plurality of past brain images Bpi, which have earlier imaging dates and times than the target brain image Bt, for the same subject. A similarity calculation unit calculates the similarity between each of the plurality of past brain images Bpi and a standard brain image Bs. A selection unit selects a reference brain image B0 serving as a reference for calculating the amount of change of the brain from the plurality of past brain images Bpi.

Abstract: A medical image processing apparatus having a processor configured to detect at least four reference landmarks among the left eye, the right eye, the diencephalon, the fornix, the corpus callosum, the left hippocampus, and the right hippocampus from a brain image, performs first registration including registration by similarity transformation using reference landmarks between the brain image and a standard brain image, and perform second registration by nonlinear transformation between the brain image and the standard brain image after the first registration.

Abstract: A medical image processing apparatus, having a processor configured to divide brains included in a brain image and a standard brain image into a plurality of regions corresponding to each other, calculate a first correction amount between the pixel value of a first reference pixel included in each of the plurality of region in the brain image and the pixel value of a second reference pixel and a second correction amount for matching first other pixel values other than the first reference pixel included in each of the plurality of regions in the brain image with pixel values of second other pixels, and correct the brain image based on the first correction amount and the second correction amount.

Abstract: A medical image display apparatus includes an image acquisition unit that receives an input of a three-dimensional brain image of a subject, a brain area division unit that divides the three-dimensional brain image of the subject into a plurality of brain areas, an image analysis unit that calculates an analysis value for each brain area from the three-dimensional brain image of the subject, a data acquisition unit that acquires information indicating a correspondence between the brain area and a function of the brain, a display unit, and a display controller that displays an image showing the brain image of the subject divided into the brain areas, a function of the brain corresponding to each of the brain areas, and the analysis value on the display unit in association with each other.

Abstract: There are provided an information output apparatus, an information output method, and an information output program capable of outputting information effective for diagnosis or evaluation of dementia. In a case where a brain area having a high atrophy rate is input, the information output apparatus can output a test item highly relevant to the input brain area using a first table T1 that stores the relevance between a plurality of divided brain areas of a brain image and a plurality of test items of a dementia diagnostic test. In addition, in a case where a test item of interest is input, a brain area highly relevant to the input test item can be output.

Abstract: The medical information display apparatus includes a first data acquisition unit that acquires a table showing relevance between at least one item included in clinical diagnostic information on dementia and a brain area, a second data acquisition unit that acquires clinical diagnostic information on dementia of a subject, an image acquisition unit that receives an input of a three-dimensional brain image, a brain area division unit that divides the three-dimensional brain image of the subject, an image analysis unit that calculates an analysis value for each brain area, an operation unit that selects one item among items included in the clinical diagnostic information of the subject, a display unit, and a display controller that specifies a brain area corresponding to the one item selected by the operation unit and displays brain area specifying information for specifying the specified brain area and an analysis value of the brain area.

Abstract: A brain image normalization apparatus, having a processor configured to: detect at least four reference landmarks of a left eye, a right eye, a diencephalon, a fornix, a corpus callosum, a left hippocampus, and a right hippocampus from a brain image including a brain of a subject; perform registration between the detected reference landmarks and reference landmarks corresponding to the detected reference landmarks included in a standard brain image; and normalize the brain image based on a result of the registration.

Abstract: A division unit 22 divides a brain included in a first brain image into a plurality of regions by performing registration between the first brain image including a brain of a subject and a standard brain image divided into a plurality of regions. A registration unit 23 performs registration between the first brain image and a second brain image that includes the brain of the subject and has a different imaging date and time from the first brain image. A change amount acquisition unit 24 acquires the amount of change from a corresponding region in the brain included in the first brain image, for at least one region of the plurality of regions in the brain included in the second brain image, based on the registration result.

Abstract: An image obtaining unit obtains actual endoscope images, and a virtual endoscope image generating unit generates virtual endoscope images including a plurality of virtual endoscope branch images. A corresponding virtual endoscope image determining unit obtains a plurality of actual endoscope images which were obtained within a predetermined amount of time before the endoscope reached its current position, compares the plurality of actual endoscope images and the plurality of virtual endoscope branch images, and determines a corresponding virtual endoscope image that corresponds to the branch structure closest to the current position of the endoscope, through which the endoscope has passed. A matching unit performs matching between each of a plurality of actual endoscope path images and a plurality of virtual endoscope path images for each of a plurality of paths. A position identifying unit identifies the current position of a leading end of the endoscope based on the results of matching.

Abstract: A three-dimensional common coordinate system is defined and a first correspondence relationship between each pixel of a first three-dimensional image which has at least a portion of a human body as a subject and coordinates on the common coordinate system is set. A second three-dimensional image which has at least a portion of the human body as a subject that at least partially overlaps the subject in the first three-dimensional image is aligned with the first three-dimensional image to calculate a correspondence relationship between pixels of the first three-dimensional image and the second three-dimensional image. A second correspondence relationship between each pixel of the second three-dimensional image and coordinates on the common coordinate system is calculated on the basis of the calculated correspondence relationship and the set first correspondence relationship. The first correspondence relationship and the second correspondence relationship are stored.

Abstract: The present disclosure provides lubricant compositions suitable for use on human tissue and effective to provide multiple sensations sequentially and/or in varying intensities. The lubricants can include a lubricating base and at least two different sensorial agents effective to impart different sensations, such as warming, cooling, tingling, refreshing, and numbing. The lubricants particularly can be suitable for use in sexual experiences so that the imparted sensations can increase and/or improve such experiences. The present disclosure further provides condoms incorporating such lubricant compositions.

Abstract: A first 3D image and a second 3D image imaged a target organ in different phases of respiration are acquired. A 3D deformation model of the target organ which is stored in advance and represents nonlinear 3D deformation of the target organ due to respiration, and which has been generated based on information about movement of the target organ due to respiration of plural patients, is read. The positions of pixels on the second 3D image representing the same positions on the target organ as plural sampled pixels in a target organ region on the first 3D image are estimated using displacement due to changes in phase of points on the 3D deformation model corresponding to the positions on the target organ represented by the pixels. Non-rigid alignment is performed between the first 3D image and the second 3D image using the estimated positions of the pixels.

Abstract: A light emitting diode (LED) tube lamp includes: a lamp tube, for receiving an external driving signal, a rectifying circuit, a filtering circuit, and an LED module coupled to the filtering circuit and configured to receive a filtered signal for emitting light, wherein the LED module comprises an LED unit, a current-limiting element for receiving the external driving signal, the current-limiting element coupled to one or more of the external connection terminals, and coupled to or in the rectifying circuit, and a ballast interface circuit coupled to the current-limiting element and having a first terminal and a second terminal, for the LED tube lamp to be compatible with a ballast providing the external driving signal, wherein the ballast interface circuit comprises a detection circuit and a switching circuit coupled to the detection circuit, and the ballast interface circuit is configured to detect whether the external driving signal comes from a ballast, and to conduct or cut off the switching circuit based

Abstract: A light emitting diode (LED) tube lamp includes: a lamp tube, for receiving an external driving signal, a rectifying circuit, a filtering circuit, and an LED module coupled to the filtering circuit and configured to receive a filtered signal for emitting light, wherein the LED module comprises an LED unit, a current-limiting element for receiving the external driving signal, the current-limiting element coupled to one or more of the external connection terminals, and coupled to or in the rectifying circuit, and a ballast interface circuit coupled to the current-limiting element and having a first terminal and a second terminal, for the LED tube lamp to be compatible with a ballast providing the external driving signal, wherein the ballast interface circuit comprises a detection circuit and a switching circuit coupled to the detection circuit, and the ballast interface circuit is configured to detect whether the external driving signal comes from a ballast, and to conduct or cut off the switching circuit based

Abstract: An image obtaining unit obtains actual endoscope images, and a virtual endoscope image generating unit generates virtual endoscope images including a plurality of virtual endoscope branch images. A corresponding virtual endoscope image determining unit obtains a plurality of actual endoscope images which were obtained within a predetermined amount of time before the endoscope reached its current position, compares the plurality of actual endoscope images and the plurality of virtual endoscope branch images, and determines a corresponding virtual endoscope image that corresponds to the branch structure closest to the current position of the endoscope, through which the endoscope has passed. A matching unit performs matching between each of a plurality of actual endoscope path images and a plurality of virtual endoscope path images for each of a plurality of paths. A position identifying unit identifies the current position of a leading end of the endoscope based on the results of matching.

Abstract: A first 3D image and a second 3D image imaged a target organ in different phases of respiration are acquired. A 3D deformation model of the target organ which is stored in advance and represents nonlinear 3D deformation of the target organ due to respiration, and which has been generated based on information about movement of the target organ due to respiration of plural patients, is read. The positions of pixels on the second 3D image representing the same positions on the target organ as plural sampled pixels in a target organ region on the first 3D image are estimated using displacement due to changes in phase of points on the 3D deformation model corresponding to the positions on the target organ represented by the pixels. Non-rigid alignment is performed between the first 3D image and the second 3D image using the estimated positions of the pixels.

Abstract: A three-dimensional common coordinate system is defined and a first correspondence relationship between each pixel of a first three-dimensional image which has at least a portion of a human body as a subject and coordinates on the common coordinate system is set. A second three-dimensional image which has at least a portion of the human body as a subject that at least partially overlaps the subject in the first three-dimensional image is aligned with the first three-dimensional image to calculate a correspondence relationship between pixels of the first three-dimensional image and the second three-dimensional image. A second correspondence relationship between each pixel of the second three-dimensional image and coordinates on the common coordinate system is calculated on the basis of the calculated correspondence relationship and the set first correspondence relationship. The first correspondence relationship and the second correspondence relationship are stored.