human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (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"):
  Abstract: The manual outlining of hepatic metastasis in (US) ultrasound acquisitions from patients suffering from pancreatic cancer is common practice. However, such pure manual measurements are often very time consuming, and the results repeatedly differ between the raters. In this contribution, we study the in-depth assessment of an interactive graph-based approach for the segmentation for pancreatic metastasis in US images of the liver with two specialists in Internal Medicine. Thereby, evaluating the approach with over one hundred different acquisitions of metastases. The two physicians or the algorithm had never assessed the acquisitions before the evaluation. In summary, the physicians first performed a pure manual outlining followed by an algorithmic segmentation over one month later. As a result, the experts satisfied in up to ninety percent of algorithmic segmentation results. Furthermore, the algorithmic segmentation was much faster than manual outlining and achieved a median Dice Similarity Coefficient (DSC) of over eighty percent. Ultimately, the algorithm enables a fast and accurate segmentation of liver metastasis in clinical US images, which can support the manual outlining in daily practice.

Includes members:
  Member "htc vive mevislab integration via openvr for medical applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "computed tomography data collection of the complete human mandible and valid clinical ground truth models")
  Member "interactive outlining of pancreatic cancer liver metastases in ultrasound images":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "algorithm guided outlining of 105 pancreatic cancer liver metastases in ultrasound")
  Member "us cut interactive algorithm for rapid detection and segmentation of liver tumors in ultrasound acquisitions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "interactive outlining of pancreatic cancer liver metastases in ultrasound images")
  Member "interactive volumetry of liver ablation zones":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "interactive outlining of pancreatic cancer liver metastases in ultrasound images")
  Member "refinement cut user guided segmentation algorithm for translational science":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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")
  Member "cube cut vertebral body segmentation in mri data through cubic shaped divergences":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "computed tomography data collection of the complete human mandible and valid clinical ground truth models")
  Member "gbm volumetry using the 3d slicer medical image computing platform":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "computed tomography data collection of the complete human mandible and valid clinical ground truth models")
  Member "integration of the openigtlink network protocol for image guided therapy with the medical platform mevislab":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "computed tomography data collection of the complete human mandible and valid clinical ground truth models")

Question: Please tell me which class the source paper 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)