1. Medical instrument, in particular a high-frequency generator for high-frequency surgery, comprising:
setting elements for presetting values and selecting functions,
functional elements for performing functions as preset by the setting elements, and additional fixed preset functions, and
at least one main controller for interrogating the setting elements and controlling the functional elements;
wherein at least one safety controller for detecting internal faults of the instrument and also external operating faults is provided;
said safety controller interrogating the setting elements, and performing interrogations concerning status information from said functional elements and said main controller, and performing plausibility checks with obtained information; and
said safety controller issuing at least one error signal in case of inadmissible conditions, and an error signal deactivating, or putting into a safe working condition, said functional elements.
2. Medical instrument according to claim 1, wherein setting elements for presetting values and selecting functions are connected exclusively to the safety controller.
3. Medical instrument according to claim 1, wherein sampling taps or sensors, connected to functional elements, are provided for transmitting information concerning instrument status exclusively to the safety controller.
4. Medical instrument according to claim 1, wherein control elements or circuit elements are provided which are exclusively controlled by the safety controller, and which can deactivate, or affect working of, the entire instrument or functional elements.
5. Medical instrument according to claim 1, wherein control elements or circuit elements which are controlled jointly by the main controller and the safety controller comprise a priority circuit that assigns a higher priority of control to the safety controller.
6. Medical instrument according to claim 1, wherein means for signaling are provided, with which the safety controller indicates an error condition or its intervention with the instrument.
7. Medical instrument according to claim 1, wherein means for telecommunication with a central unit disposed at a distance from the medical instrument are provided for signaling an error condition to the central unit, and optionally transmitting detailed status information and also additional control information or control interrogations from or to the central unit.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. An information processing device for handling data in which a topology has been formed of a plurality of nodes each having attribute values, said information processing device comprising:
a topology evaluation unit for obtaining weighting factors of edges connecting nodes, based on attribute values which neighboring nodes on the topology each have, and sorting edges based on the weighting factors; and
a node merging processing unit for extracting pairs of nodes connected by edges following the sorted order, evaluating whether or not to merge the nodes based on a predetermined statistical processing algorithm, and performing merging processing of node regions.
2. The information processing device according to claim 1, further comprising a minute node processing unit for processing minute nodes regarding which merging has not been performed sufficiently and which have been left, as the result of merging processing of nodes by said node merging processing unit.
3. The information processing device according to claim 1, wherein said topology evaluating unit appropriates difference in the attribute values which neighboring nodes each have as weighting values to edges, and performs sorting in increasing order of weighting values.
4. The information processing device according to claim 1, wherein said node merging processing unit determines whether or not to merge nodes, based on a predicate derived from the statistical concentration inequality phenomenon in the attribute values which neighboring nodes each have.
5. The information processing device according to claim 1, wherein said node merging processing unit determines that neighboring nodes f(i) and f(j) should be merged in the event that the nodes f(i) and f(j) satisfy a predicate based on the following statistical algorithm regarding statistical information Stats.f(i) and Stats.f(j) held respectively as attribute values (wherein node f(i) includes N(i) nodes and node f(j) includes N(j) nodes, function b(x) represents b(x)=(logx)Q+(Kx), K is a constant, and Q is a parameter for controlling the coarseness of the segmentations grown by merging nodes)
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6. The information processing device according to claim 1, further comprising a node attribute information holding unit for holding node attribute information relating to each node;
wherein, upon executing node merging, said node merging processing unit calculates attribute information relating to the node newly generated by merging, and performs updating processing of said node statistical information.
7. The information processing device according to claim 6, wherein said topology evaluation unit recalculates the weighting factors of the edges connecting a node subjected to merging processing and a neighboring node thereof, based on updated node attribute information, and re-sorts edges in said topology based on the weighting values;
and wherein said node merging processing unit repeatedly updates node merging and node attribute information updating, until there are no more pairs of image regions to be merged based on said statistical processing algorithm.
8. An information processing method for handling data in which a topology has been formed of a plurality of nodes each having attribute values, said method comprising:
a topology evaluation step for obtaining weighting factors of edges connecting nodes, based on attribute values which neighboring nodes on the topology each have, and sorting edges based on the weighting factors; and
a node merging processing step for extracting pairs of nodes connected by edges following the sorted order, evaluating whether or not to merge the nodes based on a predetermined statistical processing algorithm, and performing merging processing of node regions.
9. The information processing method according to claim 8, further comprising a minute node processing step for processing minute nodes regarding which merging has not been performed sufficiently and which have been left, as the result of merging processing of nodes in said node merging processing step.
10. The information processing method according to claim 8, wherein in said topology evaluating step, difference in the attribute values which neighboring nodes each have is appropriated as weighting values to edges, and sorting is performed in increasing order of weighting values.
11. The information processing method according to claim 8, wherein in said node merging processing step, whether or not to merge nodes is determined, based on a predicate derived from the statistical concentration inequality phenomenon in the attribute values which neighboring nodes each have.
12. The information processing method according to claim 8, wherein determination is made in said node merging processing step that neighboring nodes f(i) and f(j) should be merged in the event that the nodes f(i) and f(j) satisfy a predicate based on the following statistical algorithm regarding statistical information Stats.f(i) and Stats.f(j) held respectively as attribute values (wherein node f(i) includes N(i) nodes and node f(j) includes N(j) nodes, function b(x) represents b(x)=(logx)Q+(Kx), K is a constant, and Q is a parameter for controlling the coarseness of the segmentations grown by merging nodes)
Expression 2
|Stats.f(i)\u2212Stats.f(j)|2\u2266b(Ni)+b(Nj)\u2003\u2003(2).
13. The information processing method according to claim 8, further comprising a node attribute information holding step for holding node attribute information relating to each node;
wherein, in the event of executing node merging being performed, in said node merging processing step attribute information relating to the node newly generated by merging is calculated, and updating processing of said node statistical information is performed.
14. The information processing method according to claim 13, wherein in said topology evaluation step, the weighting factors of the edges connecting a node subjected to merging processing and a neighboring node thereof are recalculated, based on updated node attribute information, and re-sorts edges in said topology based on the weighting values;
and wherein in said node merging processing step, node merging and node attribute information is repeatedly updated, until there are no more pairs of image regions to be merged based on said statistical processing algorithm.
15. An information processing device for performing image processing, handling an object as a polygonal mesh made up of a plurality of polygons, said information processing device comprising:
an incidence graph input unit for inputting an incidence graph describing a polygonal mesh;
an incidence graph evaluation unit for comparing attribute values which each of image regions connected by edges has and appropriating weighting factors to the edges based on the comparison results, and sorting edges in the incidence graph based on weighting values; and
an image region mesh growing unit for extracting pairs of image regions sandwiching an edge in the sorted order, evaluating whether or not to merge the image regions based on a statistical processing algorithm, and performing mesh growing of the image regions.
16. The information processing device according to claim 15, further comprising a minute region processing unit for processing minute regions left as the result of performing mesh growing of the image regions.
17. The information processing device according to claim 15, wherein said incidence graph input unit handles individual polygons configuring a polygonal mesh as nodes, and inputs an incidence graph described connecting corresponding nodes using edges which are equivalent to the sides of neighboring polygons which are in contact.
18. The information processing device according to claim 15, wherein said incidence graph evaluation unit appropriates difference in the attribute values which the image regions connected by edges in the incidence graph each have as weighting values, and performs sorting in increasing order of weighting values.
19. The information processing device according to claim 18, wherein said incidence graph evaluation unit uses, as attribute information which image regions have, area (average area of a polygonal mesh included in an image region), normal direction, or color (average color of at least one component of RGB within the image region) or other pixel attribute information, of image regions.
20. The information processing device according to claim 15, wherein said image region mesh growing unit determines whether or not to merge image regions connected by edges in an incidence graph, based on a predicate derived from the statistical concentration inequality phenomenon in the area of polygons configuring an image region.
21. The information processing device according to claim 15, wherein said image region mesh growing unit determines the two image regions Rk and Rl connected by edges in an incidence graph are to be merged when satisfying the following predicate based on statistical algorithm (wherein the image region Rk has area Sk and is configured of nk polygons, and the image region Rl has area Sl and is configured of nl polygons, A is the largest area of the polygons, and Q is a parameter for controlling the coarseness of segmentation)
Expression 3
W(e)=|area(T1)\u2212area(T2)|\u2003\u2003(3).
22. The information processing device according to claim 21, further comprising parameter setting means for setting the parameter Q in said predicate.
23. The information processing device according to claim 22, further comprising segmentation coarseness control means for providing said parameter setting means with a parameter Q value such that a desired segmentation coarseness can be obtained.
24. The information processing device according to claim 23, wherein, upon being externally provided with a desired segmentation coarseness, said segmentation coarseness control means convert this into a parameter Q value equivalent to the coarseness, and provide this to said parameter setting means.
25. The information processing device according to claim 15, further comprising a node statistical information holding unit for holding node statistical information relating to the area of the image region corresponding to each node of the incidence graph and the number of polygons thereof;
wherein, upon executing merging of image regions, said image region mesh growing processing unit calculates the area of the image region newly generated by merging and the number of polygons, and performs updating processing of said node statistical information.
26. The information processing device according to claim 25, wherein said incidence graph evaluation unit recalculates the weighting factors of the edges connecting an image region subjected to merging processing and a neighboring image region thereof, based on updated node attribute information, and re-sorts edges in said incidence graph based on the weighting values;
and wherein said image region mesh growing processing unit repeatedly performs image region merging and node attribute information updating, until there are no more pairs of image regions to be merged based on said statistical processing algorithm.
27. The information processing device according to claim 25, wherein upon executing merging of image regions, said image region mesh growing processing unit calculates the area of the image region and the number of polygons and performs updating processing of said node statistical unit, leaving only a crust made up of polygons near the boundary of the newly-generated image region, and uses the crust for subsequent determination regarding whether or not to merge image regions.
28. The information processing device according to claim 27, wherein said image region mesh growing processing unit leaves, as a crust, the polygons near the boundary over the entire circumference of the image region newly generated by merging.
29. The information processing device according to claim 27, wherein said image region mesh growing processing unit leaves, as a crust, the polygons near the boundary where the image regions to be merged are in contact;
and upon performing mesh growing, said incidence graph evaluation unit re-evaluates the incidence graph.
30. An information processing method for performing image processing, handling an object as a polygonal mesh made up of a plurality of polygons, said method comprising:
an incidence graph input step for inputting an incidence graph describing a polygonal mesh;
an incidence graph evaluation step for comparing attribute values which each of image regions connected by edges has and appropriating weighting factors to the edges based on the comparison results, and sorting edges in the incidence graph based on weighting values; and
an image region mesh growing step for extracting pairs of image regions sandwiching an edge in the sorted order, evaluating whether or not to merge the image regions based on a statistical processing algorithm, and performing mesh growing of the image regions.
31. The information processing method according to claim 30, further comprising a minute region processing step for processing minute regions left as the result of performing mesh growing of the image regions.
32. The information processing method according to claim 30, wherein in said incidence graph input step, individual polygons configuring a polygonal mesh are handled as nodes, and an incidence graph, described connecting corresponding nodes using edges which are equivalent to the sides of neighboring polygons which are in contact, is input.
33. The information processing method according to claim 30, wherein in said incidence graph evaluation step, difference in the attribute values which the image regions connected by edges in the incidence graph each have are appropriated as weighting values, and sorting in increasing order of weighting values is performed.
34. The information processing method according to claim 33, wherein in said incidence graph evaluation step, area, normal direction, or color or other pixel attribute information, of image regions, are used as attribute information which image regions have.
35. The information processing method according to claim 30, wherein in said image region mesh growing step, whether or not to merge image regions connected by edges in an incidence graph is determined, based on a predicate derived from the statistical concentration inequality phenomenon in the area of polygons configuring an image region.
36. The information processing method according to claim 30, wherein determination is made in said image region mesh growing step that the two image regions Rk and Rl connected by edges in an incidence graph are to be merged when satisfying the following predicate based on statistical algorithm (wherein the image region Rk has area Sk and is configured of nk polygons, and the image region Rl has area Sl and is configured of nl polygons, A is the largest area of the polygons, and Q is a parameter for controlling the coarseness of segmentation)
Expression 4
w(E=(Vi,j,Vi\u2032,j\u2032))=maxC\u03b5{R,G,B}(|Ic(i,j)\u2212Ic(i\u2032,j\u2032)\u2003\u2003(4).
37. The information processing method according to claim 36, further comprising a parameter setting step for setting the parameter Q in said predicate.
38. The information processing method according to claim 37, further comprising a segmentation coarseness control step for providing said parameter setting means with a parameter Q value such that a desired segmentation coarseness can be obtained.
39. The information processing method according to claim 38, wherein, upon being externally provided with a desired segmentation coarseness, this is converted into a parameter Q value equivalent to the coarseness, and provided to said parameter setting means, in said segmentation coarseness control step.
40. The information processing method according to claim 30, further comprising a node statistical information holding step for holding node statistical information relating to the area of the image region corresponding to each node of the incidence graph and the number of polygons thereof;
wherein, upon executing merging of image regions, in said image region mesh growing processing step the area of the image region newly generated by merging and the number of polygons are calculated, and updating processing of said node statistical information is performed.
41. The information processing method according to claim 40, further comprising an incidence graph re-evaluation step for recalculating the weighting factors of the edges connecting an image region subjected to merging processing and a neighboring image region thereof, based on updated node attribute information, and re-sorting edges in said incidence graph based on the weighting values;
wherein, in said image region mesh growing processing step, image region merging and node attribute information updating is repeatedly performed, until there are no more pairs of image regions to be merged based on said statistical processing algorithm.
42. The information processing method according to claim 40, wherein upon executing merging of image regions, in said image region mesh growing processing step the area of the image region and the number of polygons is calculated and updating processing of said node statistical information is performed, leaving only a crust made up of polygons near the boundary of the newly-generated image region, and the crust is used for subsequent determination regarding whether or not to merge image regions.
43. The information processing method according to claim 42, wherein in said image region mesh growing processing step, the polygons near the boundary over the entire circumference of the image region newly generated by merging are left as a crust.
44. The information processing method according to claim 42, wherein, in said image region mesh growing processing step, the polygons near the boundary where the image regions to be merged are in contact is left as a crust;
and upon performing mesh growing, the incidence graph is re-evaluated in said incidence graph evaluation step.
45. A non-transitory computer readable medium storing a program to execute, on a computer, processing for handling data in which a topology has been formed of a plurality of nodes each having attribute values, said program causing said computer to execute:
a topology evaluation step for obtaining weighting factors of edges connecting nodes, based on attribute values which neighboring nodes on the topology each have, and sorting edges based on the weighting factors; and
a node merging processing step for extracting pairs of nodes connected by edges following the sorted order, evaluating whether or not to merge the nodes based on a predetermined statistical processing algorithm, and performing merging processing of node regions.
46. A non-transitory computer readable medium storing a program to execute, on a computer, processing for handling an object as a polygonal mesh made up of a plurality of polygons, said program causing said computer to execute:
an incidence graph input step for inputting an incidence graph describing a polygonal mesh;
an incidence graph evaluation step for comparing attribute values which each of image regions connected by edges has and appropriating weighting factors to the edges based on the comparison results, and sorting edges in the incidence graph based on weighting values; and
an image region mesh growing step for extracting pairs of image regions sandwiching an edge in the sorted order, evaluating whether or not to merge the image regions based on a statistical processing algorithm, and performing mesh growing of the image regions.