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Automated Anatomical Labeling (AAL) (or Anatomical Automatic Labeling) is a software package and digital atlas of the. It is typically used in -based research to obtain neuroanatomical labels for the locations in 3-dimensional space where the measurements of some aspect of brain function were captured. In other words, it projects the divisions in the brain atlas onto brain-shaped volumes of functional data. It is developed by a French research group based in and described further in the following: • N.

Tzourio-Mazoyer; B. Papathanassiou; F. Delcroix; & M. Joliot (January 2002). 'Automated Anatomical Labeling of activations in SPM using a Macroscopic Anatomical Parcellation of the MNI MRI single-subject brain'.. 15 (1): 273–289... The AAL program is dependent upon the and programs, but the digital human brain atlas itself can also be found elsewhere—within the program, for example.

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Currently, even when the segmentation tool is working adequately, the labeling task will be difficult because the diversity in “normal anatomical” structures can be very large. In case of missing tree segments, which will be the case in the analysis of trees with obstructions, it is even harder to perform automatic labeling. Automatic labeling also requires that the segmented tree structure is presented in an “anatomical” way. Segmentation tools often provide small branches in a standard graph-like structure.

Anatomically there will be a main branch and several sub branches that originate from that main branch. A label or anatomical name belongs to a main branch that may consist of several branching levels in the detected graph. Microsoft Visual Basic 2008 Express Edition Keygen Download.

According to another aspect of the invention, a method of updating an image with a labeled segmented object comprising image data is provided. The method comprises selecting a portion of the labeled segmented object, utilizing a pointing device. Moreover, the method comprises selecting a label in an image comprising a set of labels, utilizing the pointing device. Furthermore, the method comprises updating the label in the image with the portion of the segmented object, resulting in an updated image. In yet another aspect, an apparatus for labeling a segmented object comprising image data is provided. The apparatus comprises a pointing device configured to select a label in an image comprising a set of labels and to select a portion of the segmented object at which the label is to be positioned. The apparatus further comprises a unit configured to label the portion of the segmented object with the label by utilizing the pointing device to drag the label from the image and drop the label on the portion of the segmented object, resulting in a labeled segmented object.

In another aspect of the invention, a computer-readable medium having embodied thereon a computer program for labeling of a segmented object comprising image data, and for processing by a processor, is provided. The computer program comprises a code segment for selecting a label in an image comprising a set of labels, utilizing a pointing device. Moreover, the computer program comprises a code segment for selecting a portion of a segmented object comprising image data, at which the label is to be positioned, utilizing the pointing device.

Furthermore, the computer program comprises a code segment for labeling the portion of the segmented object with the label, resulting in a labeled segmented object. Several embodiments of the present invention will be described in more detail below with reference to the accompanying drawings in order for those skilled in the art to be able to carry out the invention. The invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. The embodiments do not limit the invention, but the invention is only limited by the appended patent claims. Furthermore, the terminology used in the detailed description of the particular embodiments illustrated in the accompanying drawings is not intended to be limiting the invention. The main idea of the present invention is to provide a method of labeling a segmented object such as a blood vessel tree.

In an embodiment, a user may select a label in an image, drag it to a portion of a segmented object, thereby selecting said portion, and drop the label at said portion. Alternatively, the user may select the label in the image, select the portion of the segmented object, and the system may be arranged to drop the selected label at the selected portion. In an embodiment, the user may select a report template suitable for reporting the findings of the current segmentation & analysis task. These medical reports often contain a “textbook” image of the studied anatomy. An anatomical image may e.g. Contain the anatomical names of the anatomical object, such as vessels, in the studied anatomy under consideration. The anatomical names may be defined as labels in the anatomical image.

The anatomical image may be used to mark the regions where a stenotic or otherwise abnormal region was found during segmentation. Next to the anatomical image a display may be used to display a rendering of the segmented object, e.g. An anatomical tree-like structure such as a vessel tree. This rendering may be a 3D rendering of the segmented volume, such as a Maximum Intensity Projection (MIP) or volume rendering, or a 3D curved planar MIP or just a 3D graph, e.g.

With line representation, of the segmented vessel tree. The only requirement to the segmented tree visualization is that enough anatomical context is visible so that the user may identify the vessels. In the following labeling step, the user may drag a label corresponding to a certain portion of the anatomical image and drop it onto a portion of the segmented object or vice versa. For example, each portion of the segmented object may e.g. Define a part of a vessel between two bifurcations. By dropping a label corresponding to a certain portion of the anatomical image onto a corresponding portion of the segmented object, the entire portion of the segmented object may be labeled. This means that not only the actual drop location in the segmented object will be labeled but also the entire portion, such as vessel part, of the segmented object will be labeled.

Accordingly, throughout this specification, by labeling is meant annotating an already segmented portion of the segmented object such that the segmented portion corresponds to an anatomical name, e.g. In an embodiment, the method may further comprise performing re-segmentation of a labeled segmented object, based on the labels of the segmented object. For example, the re-segmentation may utilize knowledge of the already labeled vessels in the segmented object.

In a practical example, the left main coronary artery in the segmented object is very short and directly bifurcates in the LAD and the LCX. Should a user already label the left main coronary artery, this information may be utilized during re-segmentation. In this case, the re-segmentation technique may utilize the fact that a split will follow soon and moreover in what directions the child branches will go.

By re-segmentation is meant that at least a part of the original segmentation is re-performed or expanded, e.g. In the event that the original segmentation (partially) failed. Segmentation techniques may fail because of bad image quality or other image artifacts. Vessel segmentation may leak into another structure or it may generate many small vessels in what is actually one bigger vessel due to image noise. If segmentation differs from an image, it may still be right, as the image might not apply for the current case.

In such a case it will be up to the user to inspect the original image data and decide on the segmentation quality. With this approach the labeling becomes part of the segmentation-cycle, which means that the user may delete branches from or add branches to the original segmented objects, or perform the labeling. This provides feedback for the automatic segmentation algorithm, which, given the anatomical textbook, has more knowledge that can be used during the re-segmentation. For example, this may signal that the original segmentation of e.g. The vessels missed some parts. From the anatomical textbook it may be known that a certain vessel should have two child branches, whereas the segmented object only comprises one, e.g.

Due to the fact that the segmentation could have missed one branch, or that the other branch might be absent, i.e. Pertain to a special case, or it might be blocked such as in the case of stenosis.

Of course not all additional branches in the originally segmented object will be wrong, as the anatomical images only show the most common situations. In another embodiment, the user may update the anatomical atlas or textbook, and extend it with a new anatomical representation, such as a special case or abnormality of the same vessel anatomy, based on a portion of the segmented object, which may be dragged-and-dropped into the anatomical atlas or textbook. Accordingly, in this embodiment the drag and drop direction has impact on whether the segmented object is to be labeled or the anatomical image is to be updated with information from the segmented object. In an embodiment, a method of updating an image with a labeled segmented object is provided. The method comprises selecting 32 a portion of the labeled segmented object, utilizing a pointing device. The method may also comprise selecting 31 a label in an image comprising a set of labels, utilizing the pointing device. Furthermore, the method may comprise updating 33 the label in the image with at least one label of the portion of the segmented object by utilizing the pointing device to drag the portion of the segmented object and drop it on the label in the image, resulting in an updated image.

The method according to some embodiments results in a labeled segmented object of an anatomical structure. The labeled segmented object may be observed by a user in order to facilitate navigation, for instance when inspecting portions, such as vessels, of the segmented object to see whether any abnormality, such as stenosis, aneurysms or plaque are visible. Inspection is facilitated as the labels in the segmented object, comprising anatomical names, will help the investigation process of the user, as different abnormalities may occur at different locations of the anatomical structure. In an embodiment, according to FIG. 4, an apparatus 40 for labeling a segmented object is provided. The apparatus comprises a pointing device 41 configured to select a label in an image comprising a set of labels. Download Infinite Stratos Season 2 Ova Sub Indo Mp4 Download more.

Moreover, the pointing device may be configured to select a portion of the segmented object at which the label is to be positioned. Furthermore, the apparatus may comprise a unit 42 for labeling the segmented object by utilizing the pointing device to drag the label from the image and drop the label on the portion of the segmented object, resulting in a labeled segmented object.

In an embodiment, according to FIG. 5, a computer-readable medium is provided having embodied thereon a computer program for processing by a processor. The computer program comprises a code segment 51 for selecting a label in an image comprising a set of labels, utilizing a pointing device. Moreover, the computer program may comprise a code segment 52 for selecting a portion of the segmented object at which the label is to be positioned, utilizing the pointing device.

Furthermore, the computer program may comprise a code segment 53 for labeling the segmented object by utilizing the pointing device to drag the label from the image and drop the label on the portion of the segmented object, resulting in a labeled segmented object. The invention may be implemented in any suitable form including hardware, software, firmware or any combination of these. However, preferably, the invention is implemented as computer software running on one or more data processors and/or digital signal processors. The elements and components of an embodiment of the invention may be physically, functionally and logically implemented in any suitable way. Indeed, the functionality may be implemented in a single unit, in a plurality of units or as part of other functional units. As such, the invention may be implemented in a single unit, or may be physically and functionally distributed between different units and processors.

In the claims, the term “comprises/comprising” does not exclude the presence of other elements or steps. Furthermore, although individually listed, a plurality of means, elements or method steps may be implemented by e.g. A single unit or processor. Additionally, although individual features may be included in different claims, these may possibly advantageously be combined, and the inclusion in different claims does not imply that a combination of features is not feasible and/or advantageous. In addition, singular references do not exclude a plurality. The terms “a”, “an”, “first”, “second” etc do not preclude a plurality. Reference signs in the claims are provided merely as a clarifying example and shall not be construed as limiting the scope of the claims in any way.