By Ananda S. Chowdhury
Recent advances in either scanning tools and aiding software program have transitioned their effect from only open air the working room to contained in the surgical theater, making intra-operative 3D imaging a reality.
This targeted text/reference examines the real software of computing device imaginative and prescient and development popularity to clinical technological know-how, with a selected specialise in reconstructive craniofacial surgical procedure. The publication discusses intensive the 2 indispensable elements of reconstructive surgical procedure; fracture detection, and reconstruction from damaged bone fragments. as well as assisting its application-oriented perspective with particular assurance of theoretical concerns, the paintings comprises worthy algorithms and correct recommendations from either graph idea and statistics.
Topics and features:
- Presents functional ideas for digital craniofacial reconstruction and computer-aided fracture detection, which could even be utilized to comparable fields similar to radiology, orthopedic surgical procedure and histopathology
- Discusses problems with picture registration, item reconstruction, combinatorial trend matching, and detection of salient issues and areas in an image
- Investigates the ideas of maximum-weight graph matching, maximum-cardinality minimum-weight matching for a bipartite graph, decision of minimal minimize in a circulate community, and building of automorphs of a cycle graph
- Examines the concepts of Markov random fields, hierarchical Bayesian recovery, Gibbs sampling, and Bayesian inference
- Includes a Foreword by way of Dr. Jack C. Yu, Milford B. Hatcher Professor of surgical procedure on the clinical collage of Georgia, Augusta, GA, USA
This useful textual content could be of serious source price to researchers and graduate scholars from a huge spectrum of disciplines together with laptop technology, electric engineering, biomedical engineering and records. scientific practitioners corresponding to plastic surgeons, orthopedic surgeons and radiologists also will locate a lot of curiosity within the ebook.
Dr. Ananda S. Chowdhury is a reader within the division of Electronics and Telecommunication Engineering at Jadavpur college, Kolkata, India. Dr. Suchendra M. Bhandarkar is a professor within the division of desktop technological know-how on the collage of Georgia, Athens, GA, USA.
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Additional info for Computer Vision-Guided Virtual Craniofacial Surgery: A Graph-Theoretic and Statistical Perspective
To improve the blood supply, one can decrease the extent of dissection. However this means not being able to visualize the entire fracture, which could lead to potential misalignments of the bone fragments. In this chapter we propose and describe a scheme that could reduce significantly the exposure time and operating time without sacrificing surgical precision. Additionally, the proposed scheme would result in a substantial reduction in the operative and postoperative trauma to the patient while decreasing significantly the cost of surgery.
Last but not the least, Ahmed et al.  have presented an approach for 3D reconstruction of the human jaw from a sequence of intra-oral images taken by a CCD camera mounted on the stylus of a hand-held digitizer that a surgeon can use to scan the inside of a patient’s mouth. A novel space carving algorithm is used to perform shape recovery for jaw reconstruction. The focus of the work is on 3D jaw reconstruction for the purpose of orthodontics with the goal of replacing the cumbersome and expensive process of creating dental casts or imprints.
However, it can be solved in polynomial time for many special graphs . Now, we state and prove a result on graph automorphisms for cycle graphs. 4 The automorphism group of a cycle graph Cn on n ≥ 3 vertices is a group of order 2n. Proof A cycle graph Cn on n ≥ 3 vertices is left fixed by exactly n rotations as well as by exactly n reflections. Thus, the resulting automorphism group has order 2n. 3 The two graphs G1 and G2 in Fig. 6 are isomorphic. The mapping from G1 to G2 is given by the following bijection: M = (A, 1), (B, 2), (C, 3), (D, 4) .
Computer Vision-Guided Virtual Craniofacial Surgery: A Graph-Theoretic and Statistical Perspective by Ananda S. Chowdhury