Introduction - Segmentation of Hand Bone for Bone Age Assessment - page 12

identification of the desired properties of segmentation framework as a result of
critical appraisal on reviewed literatures to provide direction for the top-down
strategy in designing the segmentation framework. Secondly, we describe the
proposed extension of current histogram equalization into holistic histogram
equalization. Thirdly, we present the extension of anisotropic diffusion and the
incorporation of which into the framework. Then, we present the implementation
of texture based clustering algorithm inside the module of the proposed adaptive
automated fuzzy quadruple division scheme. At last, we present the last module of
quality assurance procedure to complete the segmentation framework.
Chapter 4 discusses qualitative and quantitative analysis to justify the motiva-
tion and also evaluate the performance of each proposed module and the overall
automated segmentation framework. Each experimental result or result analysis
is followed by result discussion to interpret the implication of the result to the
research topic.
Finally, Chapter 5 summaries the research findings as well as provides sugges-
tions for exploration and extension of future research that might be relevant and
important for further development and improvement of the proposed segmentation
framework.
References
1. Tanner JM (2001) Assessment of skeletal maturity and prediction of adult height (TW3
method), W.B. Saunders, London
2. Aicardi G, Vignolo M, Milani S, Naselli A, Magliano P, Garzia P (2000) Assessment of skel-
etal maturity of the hand-wrist and knee: a comparison among methods. Am J Hum Biol
12:610-615
3. Cao F, Huang HK, Pietka E, Gilsanz V (2000) Digital hand atlas and web-based bone age
assessment: system design and implementation. Comput Med Imaging Graph 24:297-307
4. Martin DD, Heckmann C, Jenni OG, Ranke MB, Binder G, Thodberg HH (2011) Metacarpal
thickness, width, length and medullary diameter in children-reference curves from the First
Zürich longitudinal study. Osteoporos Int 22:1525-1536
5. Roche AF, French NY (1970) Differences in skeletal maturity levels between the knee and
hand. Am J Roentgenol 109:307-312
6. Chemaitilly W, Sklar CA (2010) Endocrine complications in long-term survivors of child-
hood cancers. Endocr Relat Cancer 17:R141-R159
7. Heinrich UE (1986) Significance of radiologic skeletal age determination in clinical practice.
Die Bedeutung der radiologischen Skelettalterbestimmung für die Klinik 26:212-215
8. Peloschek P, Nemec S, Widhalm P, Donner R, Birngruber E, Thodberg HH et al (2009)
Computational radiology in skeletal radiography. Eur J Radiol 72:252-257
9. Tristán-Vega A, Arribas JI (2008) A radius and ulna TW3 bone age assessment system. IEEE
Trans Biomed Eng 55:1463-1476
10. Greulich W, Pyle S (1959) Radiographic atlas of skeletal development of hand wrist
11. Tanner J, Whitehouse R (1975) Assessment of skeletal maturity and prediction of adult
height (TW2 method)
12. Aja-Fernández S, De Luis-García R, Martín-Fernández MÁ, Alberola-López C (2004) A
computational TW3 classifier for skeletal maturity assessment. A computing with words
approach. J Biomed Inform 37:99-107