Abstract: An image-based biomarker is generated using image features obtained through object-oriented image analysis of medical images. The values of a first subset of image features are measured and weighted. The weighted values of the image features are summed to calculate the magnitude of a first image-based biomarker. The magnitude of the biomarker for each patient is correlated with a clinical endpoint, such as a survival time, that was observed for the patient whose medical images were analyzed. The correlation is displayed on a graphical user interface as a scatter plot. A second subset of image features is selected that belong to a second image-based biomarker such that the magnitudes of the second image-based biomarker for the patients better correlate with the clinical endpoints observed for those patients. The second biomarker can then be used to predict the clinical endpoint of other patients whose clinical endpoints have not yet been observed.

Abstract: In a specification mode, a user specifies classes of a class network and process steps of a process hierarchy using a novel scripting language. The classes describe what the user expects to find in digital images. The process hierarchy describes how the digital images are to be analyzed. Each process step includes an algorithm and a domain that specifies the classes on which the algorithm is to operate. A Cognition Program acquires table data that includes pixel values of the digital images, as well as metadata relating to the digital images. In an execution mode, the Cognition Program generates a data network in which pixel values are linked to objects, and objects are categorized as belonging to classes. The process steps, classes and objects are linked to each other in a computer-implemented network structure in a manner that enables the Cognition Program to detect target objects in the digital images.

Abstract: A method of scanning over a substrate includes implementing a write mode of the substrate by scanning a probe across a substrate, the probe having a spring cantilever probe mechanically fixed to a probe holding structure, a tip with a nanoscale apex, and an actuator for lateral positioning of the tip; the actuator comprising a thermally switchable element and a heating element for heating the thermally switchable element; and heating the heating element to a given temperature so as to locally soften a portion of the substrate and applying a force to the softened portion of the substrate through the tip so as to create one or more indentation marks in the softened portion of the substrate.

Abstract: An analysis system analyzes digital images using a computer-implemented network structure that includes a process hierarchy, a class network and a data network. The data network includes image layers and object networks. Objects in a first object network are segmented into a first class, and objects in a second object network are segmented into a second class. One process step of the process hierarchy involves generating a third object network by imprinting objects of the first object network into the objects of the second object network such that pixel locations are unlinked from objects of the second object network to the extent that the pixel locations were also linked to objects of the first object network. The imprinting step allows object-oriented processing of digital images to be performed with fewer computations and less memory. Characteristics of an object of the third object network are then determined by measuring the object.

Abstract: An analysis system analyzes and measures patterns present in the pixel values of digital images using a computer-implemented network structure that includes a process hierarchy, a class network and a data network. The data network includes image layers, thematic layers and object networks. Various types of processing are performed depending on whether the data of the digital images is represented in the image, thematic or object layers. Pixel-oriented and object-oriented processing is combined so that fewer computations and less memory are used to analyze the digital images. Pixel-oriented processes, such as filtering, are selectively performed only at pixel locations that are assigned to a specified thematic class of a thematic layer or that are linked to a particular object of the object network. Similarly, object-oriented processing is performed at pixel locations linked to objects generated using thematic layers or using image layers on which pixel-oriented processes have already been performed.

Abstract: A method of scanning over a substrate includes implementing a write mode of the substrate by scanning a probe across a substrate, the probe having a spring cantilever probe mechanically fixed to a probe holding structure, a tip with a nanoscale apex, and an actuator for lateral positioning of the tip; the actuator comprising a thermally switchable element and a heating element for heating the thermally switchable element; and heating the heating element to a given temperature so as to locally soften a portion of the substrate and applying a force to the softened portion of the substrate through the tip so as to create one or more indentation marks in the softened portion of the substrate.

Abstract: A method is disclosed for generating an application that analyzes image data, such as from satellite and microscope pictures. The method uses a graphical user interface to add a new processing object to a processing object network. The processing object network includes a parent processing object and a child processing object. A user can append a new processing object to the child processing object or can add the new processing object as a subprocess to the parent processing object. The user selects a data domain and an algorithm from selection lists on the graphical user interface and adds them to the new processing object. The application uses a semantic cognition network to process data objects that are generated by segmenting the image data. The application then uses the new processing object to identify portions of the image that are to be highlighted on the graphical user interface.

Abstract: A system for computer-aided detection uses a computer-implemented network structure to analyze patterns present in digital image slices of a human body and to generate a three-dimensional anatomical model of a patient. The anatomical model is generated by detecting easily identifiable organs first and then using those organs as context objects to detect other organs. A user specifies membership functions that define which objects of the network structure belong to the various classes of human organs specified in a class hierarchy. A membership function of a potentially matching class determines whether a candidate object of the network structure belongs to the potential class based on the relation between a property of the voxels linked to the candidate object and a property of the context object. Some voxel properties used to classify an object are location, brightness and volume. The human organs are then measured to assist in the patient's diagnosis.

Abstract: A data storage device comprises a storage medium for storing data in the form of marks and at least one probe for scanning over a storage medium. The probe comprises a spring cantilever being during operation of the probe mechanically fixed to a probe holding structure, a tip with a nanoscale apex and an actuator for lateral positioning of the tip.

Abstract: A data storage device comprises a storage medium for storing data in the form of marks and at least one probe for scanning over a storage medium. The probe comprises a spring cantilever being during operation of the probe mechanically fixed to a probe holding structure, a tip with a nanoscale apex and an actuator for lateral positioning of the tip.

Abstract: An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.

Abstract: An analysis system analyzes and measures patterns present in the pixel values of digital images using a computer-implemented network structure that includes a process hierarchy, a class network and a data network. The data network includes image layers, thematic layers and object networks. Various types of processing are performed depending on whether the data of the digital images is represented in the image, thematic or object layers. Pixel-oriented and object-oriented processing is combined so that fewer computations and less memory are used to analyze the digital images. Pixel-oriented processes, such as filtering, are selectively performed only at pixel locations that are assigned to a specified thematic class of a thematic layer or that are linked to a particular object of the object network. Similarly, object-oriented processing is performed at pixel locations linked to objects generated using thematic layers or using image layers on which pixel-oriented processes have already been performed.

Abstract: A method and apparatus for analysis of a sample. The method includes an accessing operation for accessing a region of the sample via a tip of at least one probe mounted on a cantilever. A removing operation removes a sample material from the region that is accessed by the tip of the at least one probe mounted on the cantilever. A sensing operation senses a parameter associated to the removal of the sample material in the removing operation. The accessing, removing, and sensing operations are repeated to facilitate removal of at least one layer of the sample.

Abstract: In a specification mode, a user specifies classes of a class network and process steps of a process hierarchy using a novel scripting language. The classes describe what the user expects to find in digital images. The process hierarchy describes how the digital images are to be analyzed. Each process step includes an algorithm and a domain that specifies the classes on which the algorithm is to operate. A Cognition Program acquires table data that includes pixel values of the digital images, as well as metadata relating to the digital images. In an execution mode, the Cognition Program generates a data network in which pixel values are linked to objects, and objects are categorized as belonging to classes. The process steps, classes and objects are linked to each other in a computer-implemented network structure in a manner that enables the Cognition Program to detect target objects in the digital images.

Abstract: A method is disclosed for generating an application that analyzes image data, such as from satellite and microscope pictures. The method uses a graphical user interface to add a new processing object to a processing object network. The processing object network includes a parent processing object and a child processing object. A user can append a new processing object to the child processing object or can add the new processing object as a subprocess to the parent processing object. The user selects a data domain and an algorithm from selection lists on the graphical user interface and adds them to the new processing object. The application uses a semantic cognition network to process data objects that are generated by segmenting the image data. The application then uses the new processing object to identify portions of the image that are to be highlighted on the graphical user interface.

Abstract: Disclosed is a computer-implemented method for characterizing a complex system, wherein said complex system consists of a plurality of objects and wherein relations are present between said objects, said method comprising the steps of (a) forming a hierarchical structure having a plurality of hierarchical levels, wherein super ordinate objects of a respective higher hierarchical level of the hierarchical structure are combinations of objects of a respective lower hierarchical level of the hierarchical structure, wherein a characteristic and a boundary condition is assigned to each of said objects within the hierarchical structure; (b) forming groups of objects which belong to the same superordinate object of a respective higher hierarchical level; determining relations between objects in each respective group by taking into account the respective boundary conditions of the objects within the respective group; (d) determining at least one characteristic for each group based on the determined relations between

Abstract: A storage device including a storage medium for storing data in the form of topographic or magnetic marks. At least one probe is mounted on a common frame, the common frame and the storage medium designed for moving relative to each other for creating or detecting said marks. Each probe includes a tip facing the storage medium, a read sensing element, a write element and a capacitive platform, that forms a first electrode and is designed for a voltage potential applied to it independent from a control signal for said read sensing element and for said voltage potential applied to said capacitive platform being independent from a control signal for said write heating element. It further comprises a second electrode arranged in a fixed position relative to the storage medium forming a first capacitor together wherein said first electrode and a medium between the first and second electrode.

Abstract: A cantilever device for scanning a surface comprises a support, a tip platform and a flexible arm arrangement. The tip platform has a plurality of tips. These comprise at least two contact tips providing points of contact with a surface to be scanned, and a scanning tip for scanning the surface, where the scanning tip may be one of the two or more contact tips provided on the platform. The flexible arm arrangement connects the tip platform to the support and allows orientation of the platform, via flexing of the arm arrangement, to bring the contact tips into contact with a surface to be scanned. The platform is then at a well-defined orientation relative to the scan surface, and the scanning tip is appropriately positioned for the scanning operation. Scanning probe microscopes and data storage devices incorporating such cantilever devices are also provided.

Abstract: A transducer for detecting movement of an article mounted for movement in a plane, the transducer comprising: a heater facing the plane of movement of the article and having a temperature dependent resistance; and, an edge defined in the article between regions of different thermal conductivity; wherein, as the article describes the movement, the edge moves relative to the heater producing a corresponding variation in heat loss from the heater and a corresponding variation in resistance of the heater.

Abstract: Provides surface treatment devices, surface scanning devices, methods of operating a surface treatment device and methods of operating a surface scanning device. An area within a medium comprises at least one sharpening location for sharpening a tip of a probe mechanically. The tip is conically shaped with a radius of an apex smaller than 100 nm. In the case of the surface treatment device the probe is designed for altering the surface of the medium. In the case of the surface scanning device the probe is designed for scanning the medium. The sharpening location is suited for sharpening the tip mechanically. For that purpose the probe and the medium are being moved relative to each other such that the tip is located in the sharpening location. Then the probe and/or the medium are moved relative to each other such, that the tip is mechanically sharpened.