Abstract: An information processing apparatus includes an execution section that executes a series of processes according to an execution instruction which is formed to include a series of execution commands, and an execution control section that, in a case where execution of the series of processes by the execution section is stopped in the middle of the execution and, thereafter, is executed again, controls the execution section to not execute a first process according to a first execution command, which is decided in advance, among the series of execution commands, and to perform re-execution from a second process according to a second execution command other than the first execution command among the series of execution commands.

Abstract: An image-feature-value calculating unit extracts an image feature value of an image of a cell candidate area. An NRBC discriminating unit uses a pre-trained discriminator to identify whether or not a target cell is shown in the cell candidate area, on the basis of the image feature value of the image of the cell candidate area. When the cell candidate area is identified as an area in which a target cell is shown, a discrimination result display unit displays the image of the cell candidate area. When the cell candidate area is identified as an area in which a target cell is shown, a discriminator training unit trains the discriminator by using the image feature value of the image of the cell candidate area as a training sample on the basis of a user input about whether or not a target cell is shown in the cell candidate area.

Abstract: An image processing device 20 acquires captured images obtained by imaging a sample including a target cell, sets an object region for detecting the target cell in the captured images, extracts a plurality of cell regions each including a cell from a peripheral region including a region other than the object region, sets a range of a feature quantity of the target cell based on a feature quantity obtained from each of the plurality of cell regions, and determines whether or not the target cell is included in the object region when the feature quantity obtained from the object region is included in the set range of the feature quantity.

Abstract: A device comprises: a nucleus-candidate-region extracting section that extracts, from a captured image obtained by image-capturing a sample piece including a target cell having a nucleus, a nucleus candidate region corresponding to the nucleus; a basic-probability-information acquiring section that acquires, for each of a plurality of determination subject regions determined on the basis of the nucleus candidate region extracted by the nucleus-candidate-region extracting section, basic probability information indicating probability that an image in the determination subject region is an image of the target cell, on the basis of a feature amount of the image of the determination subject region; and a probability-information calculating section that calculates probability information indicating probability that an image in a display subject region corresponding to the nucleus candidate region is the image of the target cell, on the basis of the basic probability information acquired for each of the plurality of

Abstract: An image processing device 20 acquires captured images obtained by imaging a sample including a target cell, performs machine learning based on a first image feature quantity, sets a plurality of object regions for detecting the target cell in the captured images, and displays the plurality of object regions in an order determined based on the first image feature quantity of each of the plurality of object regions. The image processing device 20 calculates a second image feature quantity in each of the plurality of object regions, sorts the plurality of displayed object regions in an order of the second image feature quantity similar to the second image feature quantity of a reference object region selected from among the plurality of object regions, and displays the plurality of object regions.

Abstract: An image processing device sets a determination target area based on a pixel to a taken image for each of a plurality of pixels included in a pixel group obtained as a candidate of a nucleus of a target cell, and determines whether or not the target cell is included in the determination target area, which is set by the setting section for each of the plurality of pixels included in the pixel group, based on whether or not an image feature amount obtained from the determination target area satisfies a condition of the image feature amount of the target cell.

Abstract: A device comprises: a nucleus-candidate-region extracting section that extracts, from a captured image obtained by image-capturing a sample piece including a target cell having a nucleus, a nucleus candidate region corresponding to the nucleus; a basic-probability-information acquiring section that acquires, for each of a plurality of determination subject regions determined on the basis of the nucleus candidate region extracted by the nucleus-candidate-region extracting section, basic probability information indicating probability that an image in the determination subject region is an image of the target cell, on the basis of a feature amount of the image of the determination subject region; and a probability-information calculating section that calculates probability information indicating probability that an image in a display subject region corresponding to the nucleus candidate region is the image of the target cell, on the basis of the basic probability information acquired for each of the plurality of

Abstract: An image-feature-value calculating unit extracts an image feature value of an image of a cell candidate area. An NRBC discriminating unit uses a pre-trained discriminator to identify whether or not a target cell is shown in the cell candidate area, on the basis of the image feature value of the image of the cell candidate area. When the cell candidate area is identified as an area in which a target cell is shown, a discrimination result display unit displays the image of the cell candidate area. When the cell candidate area is identified as an area in which a target cell is shown, a discriminator training unit trains the discriminator by using the image feature value of the image of the cell candidate area as a training sample on the basis of a user input about whether or not a target cell is shown in the cell candidate area.

Abstract: An image processing device 20 acquires captured images obtained by imaging a sample including a target cell, sets an object region for detecting the target cell in the captured images, extracts a plurality of cell regions each including a cell from a peripheral region including a region other than the object region, sets a range of a feature quantity of the target cell based on a feature quantity obtained from each of the plurality of cell regions, and determines whether or not the target cell is included in the object region when the feature quantity obtained from the object region is included in the set range of the feature quantity.

Abstract: An image processing device 20 acquires captured images obtained by imaging a sample including a target cell, performs machine learning based on a first image feature quantity, sets a plurality of object regions for detecting the target cell in the captured images, and displays the plurality of object regions in an order determined based on the first image feature quantity of each of the plurality of object regions. The image processing device 20 calculates a second image feature quantity in each of the plurality of object regions, sorts the plurality of displayed object regions in an order of the second image feature quantity similar to the second image feature quantity of a reference object region selected from among the plurality of object regions, and displays the plurality of object regions.

Abstract: An image processing device sets a determination target area based on a pixel to a taken image for each of a plurality of pixels included in a pixel group obtained as a candidate of a nucleus of a target cell, and determines whether or not the target cell is included in the determination target area, which is set by the setting section for each of the plurality of pixels included in the pixel group, based on whether or not an image feature amount obtained from the determination target area satisfies a condition of the image feature amount of the target cell.

Abstract: A job execution apparatus includes a partial job allocation processing section and a partial job execution instruction section. The partial job allocation processing section allocates each partial job formed by segmenting a received job to a data processing apparatus capable of executing the partial job. The partial job execution instruction section instructs the data processing apparatus to execute the partial job. The partial job allocation processing section reallocates a partial job, which execution was not completed by the data processing apparatus to which the partial job is allocated until a preset end time, to a data processing apparatus capable of executing the unfinished partial job, other than the data processing apparatus to which the unfinished partial job is allocated. The partial job execution instruction section transmits an instruction for executing the unfinished partial job to the reallocated data processing apparatus.

Abstract: An image processing apparatus according to an aspect of the invention includes a first storage unit, a second storage unit, a control unit, and a construction unit. A program of at least one module including a buffer module among modules of an image processing unit is stored in the first storage unit. An image processing program and a shared library can be additionally stored in the second storage unit. The image processing program is used to perform image processing and a program of a module generation unit is registered in the shared library. The control unit instructs at least one module in the image processing unit to perform image processing during construction of the image processing unit. The construction unit constructs the image processing unit.

Abstract: A job execution apparatus includes a partial job allocation processing section and a partial job execution instruction section. The partial job allocation processing section allocates each partial job formed by segmenting a received job to a data processing apparatus capable of executing the partial job. The partial job execution instruction section instructs the data processing apparatus to execute the partial job. The partial job allocation processing section reallocates a partial job, which execution was not completed by the data processing apparatus to which the partial job is allocated until a preset end time, to a data processing apparatus capable of executing the unfinished partial job, other than the data processing apparatus to which the unfinished partial job is allocated. The partial job execution instruction section transmits an instruction for executing the unfinished partial job to the reallocated data processing apparatus.

Abstract: A processing device has plural processing modules executing a processing; and plural connectors each having a linking section, an associating section, and a controller. The linking section is able to link with at least one other connector at an input side or an output side. The associating section associates the connector with one of the processing modules. In accordance with a linked state, the controller controls the processing module associated by the associating section.

Abstract: A processing device has plural processing modules executing a processing; and plural connectors each having a linking section, an associating section, and a controller. The linking section is able to link with at least one other connector at an input side or an output side. The associating section associates the connector with one of the processing modules. In accordance with a linked state, the controller controls the processing module associated by the associating section.

Abstract: A processing device has plural processing modules executing a processing; and plural connectors each having a linking section, an associating section, and a controller. The linking section is able to link with at least one other connector at an input side or an output side. The associating section associates the connector with one of the processing modules. In accordance with a linked state, the controller controls the processing module associated by the associating section.

Abstract: An image processing device including a storage section, a parallel processing controller, a sequential processing controller, and a selection section which selectively operates the two control sections. The parallel processing controller connects one or more of the image processing modules such that first buffer modules are connected at least one of preceding and following each image processing module, to formulate a first image processing section, and controls such that individual image processing modules perform image processing in parallel with one another. The first buffer modules perform exclusive access control. The sequential processing controller connects one or more of the image processing modules such that second buffer modules are connected at least one of preceding and following each image processing module, to formulate a second image processing section, and controls such that the individual image processing modules perform image processing sequentially.

Abstract: An image processing device has an image processing module and a buffer module. The image processing module has an image processing engine that carries out an image processing on image data. The buffer module has a buffer that stores the image data and a buffer control section that controls the amount of the image data to input into a following image processing module.

Abstract: An image processing device including an image processing section having one or more image processing modules and buffer modules having a buffer is provided. The buffer module, recognizes a number of image processing modules which are connected at the following stage of its own module; stores, for each of the following image processing modules, a head position of un-read image data among image data which is stored in the buffer; and each time image data is requested from an following image processing module, causes the image processing module to read, in a read data amount which is set in advance for its own module at each of the individual following image processing modules or which is designated each time of the request, image data which is stored in the buffer, from the head position corresponding to the image processing module.