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 "clinical evaluation of semi automatic open source algorithmic software segmentation of the mandibular bone practical feasibility and assessment of a new course of action"):
  Abstract: Introduction #R##N#Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However—due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice.#R##N##R##N##R##N#Material and methods #R##N#In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance.#R##N##R##N##R##N#Results #R##N#Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p  0.94) for any of the comparison made between the two groups.#R##N##R##N##R##N#Discussion #R##N#Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a greater data amount are areas of future works.

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 "a semi automatic computer aided method for surgical template design":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "computer aided position planning of miniplates to treat facial bone defects")
  Member "refinement cut user guided segmentation algorithm for translational science":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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")
  Member "cube cut vertebral body segmentation in mri data through cubic shaped divergences":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (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-6 (induced by source paper "computed tomography data collection of the complete human mandible and valid clinical ground truth models")
  Member "pcg cut graph driven segmentation of the prostate central gland":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gland instance segmentation using deep multichannel neural networks")
  Member "pituitary adenoma volumetry with 3d slicer":
    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)