human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "detection and visualization of endoleaks in ct data for monitoring of thoracic and abdominal aortic aneurysm stents"
  Abstract: In this paper we present an efficient algorithm for the segmentation of the inner and outer boundary of thoratic and abdominal aortic aneurysms (TAA & AAA) in computed tomography angiography (CTA) acquisitions. The aneurysm segmentation includes two steps: first, the inner boundary is segmented based on a grey level model with two thresholds; then, an adapted active contour model approach is applied to the more complicated outer boundary segmentation, with its initialization based on the available inner boundary segmentation. An opacity image, which aims at enhancing important features while reducing spurious structures, is calculated from the CTA images and employed to guide the deformation of the model. In addition, the active contour model is extended by a constraint force that prevents intersections of the inner and outer boundary and keeps the outer boundary at a distance, given by the thrombus thickness, to the inner boundary. Based upon the segmentation results, we can measure the aneurysm size at each centerline point on the centerline orthogonal multiplanar reformatting (MPR) plane. Furthermore, a 3D TAA or AAA model is reconstructed from the set of segmented contours, and the presence of endoleaks is detected and highlighted. The implemented method has been evaluated on nine clinical CTA data sets with variations in anatomy and location of the pathology and has shown promising results.

Connected through hyperedge HE-1 (induced by source paper "clinical evaluation of semi automatic open source algorithmic software segmentation of the mandibular bone practical feasibility and assessment of a new course of action"):
  with members:
    - "htc vive mevislab integration via openvr for medical applications"
    - "a semi automatic computer aided method for surgical template design"
    - "refinement cut user guided segmentation algorithm for translational science"
    - "cube cut vertebral body segmentation in mri data through cubic shaped divergences"
    - "gbm volumetry using the 3d slicer medical image computing platform"
    - "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab"
    - "pcg cut graph driven segmentation of the prostate central gland"
    - "pituitary adenoma volumetry with 3d slicer"

Connected through hyperedge HE-2 (induced by source paper "in depth assessment of an interactive graph based approach for the segmentation for pancreatic metastasis in ultrasound acquisitions of the liver with two specialists in internal medicine"):
  with members:
    - "htc vive mevislab integration via openvr for medical applications"
    - "interactive outlining of pancreatic cancer liver metastases in ultrasound images"
    - "us cut interactive algorithm for rapid detection and segmentation of liver tumors in ultrasound acquisitions"
    - "interactive volumetry of liver ablation zones"
    - "refinement cut user guided segmentation algorithm for translational science"
    - "cube cut vertebral body segmentation in mri data through cubic shaped divergences"
    - "gbm volumetry using the 3d slicer medical image computing platform"
    - "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab"

Connected through hyperedge HE-3 (induced by source paper "computer aided position planning of miniplates to treat facial bone defects"):
  with members:
    - "htc vive mevislab integration via openvr for medical applications"
    - "a semi automatic computer aided method for surgical template design"
    - "cube cut vertebral body segmentation in mri data through cubic shaped divergences"
    - "gbm volumetry using the 3d slicer medical image computing platform"
    - "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab"
    - "pcg cut graph driven segmentation of the prostate central gland"
    - "pituitary adenoma volumetry with 3d slicer"

Connected through hyperedge HE-4 (induced by source paper "htc vive mevislab integration via openvr for medical applications"):
  with members:
    - "interactive volumetry of liver ablation zones"
    - "cube cut vertebral body segmentation in mri data through cubic shaped divergences"
    - "gbm volumetry using the 3d slicer medical image computing platform"
    - "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab"
    - "pcg cut graph driven segmentation of the prostate central gland"
    - "pituitary adenoma volumetry with 3d slicer"
    - "square cut a segmentation algorithm on the basis of a rectangle shape"

Connected through hyperedge HE-5 (induced by source paper "interactive and scale invariant segmentation of the rectum sigmoid via user defined templates"):
  with members:
    - "interactive volumetry of liver ablation zones"
    - "refinement cut user guided segmentation algorithm for translational science"
    - "development of an open source software module for enhanced visualization during mr guided interstitial gynecologic brachytherapy"
    - "cube cut vertebral body segmentation in mri data through cubic shaped divergences"
    - "gbm volumetry using the 3d slicer medical image computing platform"
    - "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab"
    - "pcg cut graph driven segmentation of the prostate central gland"
    - "image guided therapy system for interstitial gynecologic brachytherapy in a multimodality operating suite"

Connected through hyperedge HE-6 (induced by source paper "cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures"):
  with members:
    - "interactive volumetry of liver ablation zones"
    - "refinement cut user guided segmentation algorithm for translational science"
    - "development of an open source software module for enhanced visualization during mr guided interstitial gynecologic brachytherapy"
    - "cube cut vertebral body segmentation in mri data through cubic shaped divergences"
    - "gbm volumetry using the 3d slicer medical image computing platform"
    - "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab"
    - "image guided therapy system for interstitial gynecologic brachytherapy in a multimodality operating suite"
    - "template cut a pattern based segmentation paradigm"

Connected through hyperedge HE-7 (induced by source paper "us cut interactive algorithm for rapid detection and segmentation of liver tumors in ultrasound acquisitions"):
  with members:
    - "interactive volumetry of liver ablation zones"
    - "refinement cut user guided segmentation algorithm for translational science"
    - "cube cut vertebral body segmentation in mri data through cubic shaped divergences"
    - "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab"
    - "template cut a pattern based segmentation paradigm"
    - "square cut a segmentation algorithm on the basis of a rectangle shape"
    - "aorta segmentation for stent simulation"
    - "a flexible semi automatic approach for glioblastoma multiforme segmentation"

Connected through hyperedge HE-8 (induced by source paper "interactive volumetry of liver ablation zones"):
  with members:
    - "gbm volumetry using the 3d slicer medical image computing platform"
    - "pcg cut graph driven segmentation of the prostate central gland"
    - "pituitary adenoma volumetry with 3d slicer"
    - "aorta segmentation for stent simulation"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CV(Computer Vision and Pattern Recognition)