Abstract: In one aspect the present invention relates to a system 100 for automated extraction of multi-cellular physiological parameters. The system 100 comprises a morphogenesis module 160 for growing a plurality of cells, a monitoring unit 110 for monitoring the plurality of cells, a controller 140 for controlling the morphogenesis module 160 and the monitoring unit 110 to grow the plurality of cells and analyse the growth of the plurality of cells in order to determine the multi-cellular physiological parameters, the controller (140) further comprising a process modelling unit (146) for determining inter-cellular interactions in response to various process conditions. The multi-cellular physiological parameters may provide an optimised protocol for growing various tissue types. A further aspect of the present invention provides a method 200 for automated extraction of multi-cellular physiological parameters.

Abstract: A system for performing automated cell screening in drug discovery, includes an automated microscope, a fast autofocus device, and a digital imaging system. Processes are implemented in software through which relevant cellular material is segmented and quantified with minimal user interaction. Improvements in the following areas: known methods for image processing are implemented in such a way that automated segmentation is achieved; sets of known measurements (pixel counting, etc.) are implemented as methods which demonstrate aspects of biology in a reliable fashion; components for automated positioning, focusing, imaging and processing of a multiplicity of samples are integrated as systems within which the segmentation and measurement methods may be mounted; and components and methods are adapted into systems which yield more highly automated and more rapid cell screening.

Abstract: In one aspect, the present invention relates to a system 100 for automated cellular assay data analysis. The system 100 comprises a virtual assay module (VAM) 115 operable to generate simulated images of cell responses to one or more stimuli. The system 100 also comprises a comparator module 116 operable to compare the actual and simulated images, and an analysis module 117 operable to quantify the differences between phenotypes represented by the actual and simulated images. Various aspects and embodiments of present invention may account for stochastic variations in the response of single cells, to provide additional useful information relating to, for example, toxological effects and/or for use as part of a feedback mechanism to refine dynamically a virtual assay model such that it is not limited by way of there being only inadequate static fitting expressions available.

Abstract: According to one aspect, the present invention relates to an imaging system 100 for enhancing microscopic images of unstained cells. The imaging system 100 comprises a light source 102 for producing light 120a, a sample holder 109 for containing cells to be imaged, a condenser 104 for focussing the light 120b at a focal plane within the sample holder 109 on the cells to be imaged, a translation mechanism for moving the focal plane of the light 120b relative to the sample holder 109 and a detector system 112 configured to acquire a plurality of images at respective focal planes within the sample holder 109 and process the plurality of images to provide an enhanced processed imaged.

Abstract: A first aspect of the invention relates to an apparatus 100 for genotoxicological screening. The apparatus 100 comprises a processor 114 for analyzing images. The processor 114 is configured to provide an identifier module 115 for identifying target cells in an image and a dynamically modifiable classifier module 116 for classifying the identified cells in accordance with one or more phenotype, such as micronuclei, for example. The processor 114 is also configured to provide a scoring module 117 for assigning respective confidence measurements to the classified cells. Various aspects and embodiments of the invention may be used, for example, to provide for improved reliability and accuracy when performing automated high-throughput screening (HTS) drug assays.

Abstract: In one aspect, the present invention relates to a system 100 for automated cellular assay data analysis. The system 100 comprises a virtual assay module (VAM) 115 operable to generate simulated images of cell responses to one or more stimuli. The system 100 also comprises a comparator module 116 operable to compare the actual and simulated images, and an analysis module 117 operable to quantify the differences between phenotypes represented by the actual and simulated images. Various aspects and embodiments of present invention may account for stochastic variations in the response of single cells, to provide additional useful information relating to, for example, toxological effects and/or for use as part of a feedback mechanism to refine dynamically a virtual assay model such that it is not limited by way of there being only inadequate static fitting expressions available.

Abstract: A first aspect of the invention relates to an apparatus 100 for genotoxicological screening. The apparatus 100 comprises a processor 114 for analysing images. The processor 114 is configured to provide an identifier module 115 for identifying target cells in an image and a dynamically modifiable classifier module 116 for classifying the identified cells in accordance with one or more phenotype, such as micronuclei, for example. The processor 114 is also configured to provide a scoring module 117 for assigning respective confidence measurements to the classified cells. Various aspects and embodiments of the invention may be used, for example, to provide for improved reliability and accuracy when performing automated high-throughput screening (HTS) drug assays.

Abstract: In one aspect the present invention relates to a system 100 for automated extraction of multi-cellular physiological parameters. The system 100 comprises a morphogenesis module 160 for growing a plurality of cells, a monitoring unit 110 for monitoring the plurality of cells, a controller 140 for controlling the morphogenesis module 160 and the monitoring unit 110 to grow the plurality of cells and analyse the growth of the plurality of cells in order to determine the multi-cellular physiological parameters, the controller (140) further comprising a process modeling unit (146) for determining inter-cellular interactions in response to various process conditions. The multi-cellular physiological parameters may provide an optimised protocol for growing various tissue types. A further aspect of the present invention provides a method 200 for automated extraction of multi-cellular physiological parameters.

Abstract: A method of processing an input image produces an output image emphasizing peak-like structures. The input image comprises input pixels and each input pixel has an intensity characteristic. The output image comprises corresponding output pixels and each output pixel has a value. The method comprises the step of calculating for an input pixel the second derivative of the intensity characteristic in two orthogonal directions, one of the directions being the direction of maximum curvature. The product of the two second derivatives is calculated and the value of the output pixel corresponding to the input pixel is determined in dependence on the product.

Abstract: A computer-implemented method of performing image processing for images of biological objects includes: storing definitions of a plurality of descriptors; receiving image data relating to an image of a reference population of biological objects; receiving image data relating to an image of a target population of biological objects; processing the reference population image data to obtain a reference set of measurements, containing data for each of the descriptors; processing the target population image data to obtain a target set of measurements, containing data for each of the descriptors; and selecting a combination of the descriptors on the basis of comparing the reference set with the target set to define a preferred combination of the descriptors for use in identifying characteristics of a further population of biological objects which are similar to those of the target population.

Abstract: According to one aspect, the present invention relates to an imaging system 100 for enhancing microscopic images of unstained cells. The imaging system 100 comprises a light source 102 for producing light 120a, a sample holder 109 for containing cells to be imaged, a condenser 104 for focussing the light 120b at a focal plane within the sample holder 109 on the cells to be imaged, a translation mechanism for moving the focal plane of the light 120b relative to the sample holder 109 and a detector system 112 configured to acquire a plurality of images at respective focal planes within the sample holder 109 and process the plurality of images to provide an enhanced processed imaged.

Abstract: A system for performing automated cell screening in drug discovery, includes an automated microscope, a fast autofocus device, and a digital imaging system. Processes are implemented in software through which relevant cellular material is segmented and quantified with minimal user interaction. Improvements in the following areas: known to methods for image processing are implemented in such a way that automated segmentation is achieved; sets of known measurements (pixel counting, etc.) are implemented as methods which demonstrate aspects of biology in a reliable fashion; components for automated positioning, focusing, imaging and processing of a multiplicity of samples are integrated as systems within which the segmentation and measurement methods may be mounted; and components and methods are adapted into systems which yield more highly automated and more rapid cell screening.

Abstract: A system for performing automated cell screening in drug discovery, includes an automated microscope, a fast autofocus device, and a digital imaging system. Processes are implemented in software through which relevant cellular material is segmented and quantified with minimal user interaction. Improvements in the following areas: known methods for image processing are implemented in such a way that automated segmentation is achieved; sets of known measurements (pixel counting, etc.) are implemented as methods which demonstrate aspects of biology in a reliable fashion; components for automated positioning, focusing, imaging and processing of a multiplicity of samples are integrated as systems within which the segmentation and measurement methods may be mounted; and components and methods are adapted into systems which yield more highly automated and more rapid cell screening.

Abstract: A system for performing automated cell screening in drug discovery, includes an automated microscope, a fast autofocus device, and a digital imaging system. Processes are implemented in software through which relevant cellular material is segmented and quantified with minimal user interaction. Improvements in the following areas: known methods for image processing are implemented in such a way that automated segmentation is achieved; sets of known measurements (pixel counting, etc.) are implemented as methods which demonstrate aspects of biology in a reliable fashion; components for automated positioning, focusing, imaging and processing of a multiplicity of samples are integrated as systems within which the segmentation and measurement methods may be mounted; and components and methods are adapted into systems which yield more highly automated and more rapid cell screening.

Abstract: A system for performing automated cell screening in drug discovery, including an automated microscope, a fast autofocus device and a digital imaging system. Processes are implemented in software through which relevant cellular material is segmented and quantified with minimal user interaction. Improvements in the following areas: known methods for image processing are implemented in such a way that automated segmentation is achieved; sets of known measurements (pixel counting, etc.) are implemented as methods which demonstrate aspects of biology in a reliable fashion; components for automated positioning, focusing, imaging and processing of a multiplicity of samples are integrated as systems within which the segmentation and measurement methods may be mounted; and components and methods are adapted into systems which yield more highly automated and more rapid cell screening.

Abstract: A method of processing an input image produces an output image emphasising peak-like structures. The input image comprises input pixels and each input pixel has an intensity characteristic. The output image comprises corresponding output pixels and each output pixel has a value. The method comprises the step of calculating for an input pixel the second derivative of the intensity characteristic in two orthogonal directions, one of the directions being the direction of maximum curvature. The product of the two second derivatives is calculated and the value of the output pixel corresponding to the input pixel is determined in dependence on the product.

Abstract: A computer-implemented method of performing image processing for images of biological objects includes: storing definitions of a plurality of descriptors; receiving image data relating to an image of a reference population of biological objects; receiving image data relating to an image of a target population of biological objects; processing the reference population image data to obtain a reference set of measurements, containing data for each of the descriptors; processing the target population image data to obtain a target set of measurements, containing data for each of the descriptors; and selecting a combination of the descriptors on the basis of comparing the reference set with the target set to define a preferred combination of the descriptors for use in identifying characteristics of a further population of biological objects which are similar to those of the target population.

Abstract: A method of classifying cells into subpopulations using cell classifying data is described. The method comprises receiving and analyzing image data to identify object areas in the image data to determine, for at least one selected first cell, one or more measurements. A first parameter set is derived from the measurements for the first cell, the first parameter set comprising at least one of said one or more measurements. The first set of cells are classified into subpopulations, and identified to produce first identifying data. Cell classifying data for use in classifying a second set of cells into subpopulations is derived from the first parameter set and the first identifying data. A second set of cells is classified into subpopulations on the basis of one or more measurements taken for cells in the second set of cells, by use of the cell classifying data. The parameter sets of cells may be represented as vectors in an n-dimensional space.

Abstract: A system for performing automated cell screening in drug discovery, including an automated microscope, a fast autofocus device and a digital imaging system. Processes are implemented in software through which relevant cellular material is segmented and quantified with minimal user interaction. Improvements in the following areas: known methods for image processing are implemented in such a way that automated segmentation is achieved; sets of known measurements (pixel counting, etc.) are implemented as methods which demonstrate aspects of biology in a reliable fashion; components for automated positioning, focusing, imaging and processing of a multiplicity of samples are integrated as systems within which the segmentation and measurement methods may be mounted; and components and methods are adapted into systems which yield more highly automated and more rapid cell screening.

Abstract: A method of classifying cells into subpopulations using cell classifying data is described. The method comprises receiving and analyzing image data to identify object areas in the image data to determine, for at least one selected first cell, one or more measurements. A first parameter set is derived from the measurements for the first cell, the first parameter set comprising at least one of said one or more measurements. The first set of cells are classified into subpopulations, and identified to produce first identifying data. Cell classifying data for use in classifying a second set of cells into subpopulations is derived from the first parameter set and the first identifying data. A second set of cells is classified into subpopulations on the basis of one or more measurements taken for cells in the second set of cells, by use of the cell classifying data. The parameter sets of cells may be represented as vectors in an n-dimensional space.