A.A.T. Bui et al One can assume that every picture including medical images- contain a huge amount of information and knowledge that must be extracted and organized. Knowl edge can be conveniently categorized twofold [16]: implicit, which represents a given individual's acumen and experience; and explicit, which characterizes generally accepted facts. Clearly, im owledge is advanced through current informatics endeavors, as employed by the individual scientist and clinician. But informatics can further serve to create explicit knowledge by combining together the implicit knowl edge from across a large number of sources. In the context of healthcare, individual physician practices and the decisions made in routine patient care can be brought together to generate new scientific insights. That is to say that medical imaging informatics can provide the transformative process through which medical practice nvolving imaging can lead to new explicit knowledge. Informatics research can lead to means to standardize image content, enabling comparisons across populations and facilitate new ways of thinking References 1. Aberegg SK, Terry PB(2004)Medical decision-making and healthcare disparities: The physicians role. J Lab Clin Med, 144(1): 11-17. 2. American College of Radiology(ACr)(2005)ACR chair tells House Committee unneces- sary and inferior medical imaging lowers quality of care, costs taxpayers. American CollegeofRadiology.http:/www.acr.org.AccessedApril23,2009 3. Berbaum KS, Franken EA, Jr, Dorfman DD, Lueben KR(1994) Influence of clinical his- tory on perception of abnormalities in pediatric radiographs. Acad Radiol, 1(3): 217-223 4. Bui AA, Taira RK, Goldman D, Dionisio JD, Aberle DR, El-Saden S, Sayre J, Rice T, Kangarloo H(2004) Effect of an imaging-based streamlined electronic healthcare process on quality and costs. Acad Radiol, 11(1): 13-20 5. Clayman CB, Curry RH (1992) The American Medical Association Guide to Your Familys Symptoms. 1st updated pbk. edition. Random House, New York 6. Croskerry P(2002)Achieving quality in clinical decision making: Cognitive strategies and detection of bias. Acad Emerg Med, 9(11): 1184-1204. 7. DeWalt DA, Rothrock N, Yount S, Stone AA(2007)Evaluation of item candidates: The PROMIS qualitative item review. Med Care, 45(5 Suppl 1): S12-21 8. Dwyer Ill SJ(2000)A personalized view of the history of PACS in the USA. Medical Imaging 2000: PACS Design and Evaluation: Engineering and Clinical Issues, vol 3980 SPIE, San Diego, CA, USA, pp 2-9 Edep ME, Shah NB, Tateo IM, Massie BM (1997) Differences between primary care phy sicians and cardiologists in management of congestive heart failure: Relation to practice :518-526. 10. Greenes RA (2007)A brief history of clinical decision support: Technical, social, cultural, economic, and governmental perspectives. In: Greenes RA (ed) Clinical Decision Support The road ahead. elsevier academic press. Boston ma. 11. Huang HK (2004)PACS and Imaging Informatics: Basic Principles and Applications. 2nd edition. Wiley-Liss, Hoboken, NJ 12. Kangarloo H, Valdez JA, Yao L, Chen S, Curran J, Goldman D, Sinha U, Dionisio JD, Taira R, Sayre J, Seeger L, Johnson R, Barbaric Z, Steckel R(2000) Improving the quality of care through routine teleradiology consultation. Acad Radiol, 7(3): 149-155 13. Kansal AR, Torquato S, Harsh GI, Chiocca EA, Deisboeck TS(2000) Simulated brain tumor growth dynamics using a three-dimensional cellular automaton. J Theor BioL, 203(4):367-38212 A.A.T. Bui et al. One can assume that every picture – including medical images – contain a huge amount of information and knowledge that must be extracted and organized. Knowl￾edge can be conveniently categorized twofold [16]: implicit, which represents a given individual’s acumen and experience; and explicit, which characterizes generally accepted facts. Clearly, implicit knowledge is advanced through current informatics endeavors, as employed by the individual scientist and clinician. But informatics can further serve to create explicit knowledge by combining together the implicit knowl￾edge from across a large number of sources. In the context of healthcare, individual physician practices and the decisions made in routine patient care can be brought together to generate new scientific insights. That is to say that medical imaging informatics can provide the transformative process through which medical practice involving imaging can lead to new explicit knowledge. Informatics research can lead to means to standardize image content, enabling comparisons across populations and facilitate new ways of thinking. References 1. Aberegg SK, Terry PB (2004) Medical decision-making and healthcare disparities: The physician’s role. J Lab Clin Med, 144(1):11-17. 2. American College of Radiology (ACR) (2005) ACR chair tells House Committee unneces￾sary and inferior medical imaging lowers quality of care, costs taxpayers. American College of Radiology. http://www.acr.org. Accessed April 23, 2009. 3. Berbaum KS, Franken EA, Jr., Dorfman DD, Lueben KR (1994) Influence of clinical his￾tory on perception of abnormalities in pediatric radiographs. Acad Radiol, 1(3):217-223. 4. Bui AA, Taira RK, Goldman D, Dionisio JD, Aberle DR, El-Saden S, Sayre J, Rice T, Kangarloo H (2004) Effect of an imaging-based streamlined electronic healthcare process on quality and costs. Acad Radiol, 11(1):13-20. 5. Clayman CB, Curry RH (1992) The American Medical Association Guide to Your Family’s Symptoms. 1st updated pbk. edition. Random House, New York. 6. Croskerry P (2002) Achieving quality in clinical decision making: Cognitive strategies and detection of bias. Acad Emerg Med, 9(11):1184-1204. 7. DeWalt DA, Rothrock N, Yount S, Stone AA (2007) Evaluation of item candidates: The PROMIS qualitative item review. Med Care, 45(5 Suppl 1):S12-21. 8. Dwyer III SJ (2000) A personalized view of the history of PACS in the USA. Medical Imaging 2000: PACS Design and Evaluation: Engineering and Clinical Issues, vol 3980. SPIE, San Diego, CA, USA, pp 2-9. 9. Edep ME, Shah NB, Tateo IM, Massie BM (1997) Differences between primary care phy￾sicians and cardiologists in management of congestive heart failure: Relation to practice guidelines. J Am Coll Cardiol, 30(2):518-526. 10. Greenes RA (2007) A brief history of clinical decision support: Technical, social, cultural, economic, and governmental perspectives. In: Greenes RA (ed) Clinical Decision Support: The Road Ahead. Elsevier Academic Press, Boston, MA. 11. Huang HK (2004) PACS and Imaging Informatics: Basic Principles and Applications. 2nd edition. Wiley-Liss, Hoboken, NJ. 12. Kangarloo H, Valdez JA, Yao L, Chen S, Curran J, Goldman D, Sinha U, Dionisio JD, Taira R, Sayre J, Seeger L, Johnson R, Barbaric Z, Steckel R (2000) Improving the quality of care through routine teleradiology consultation. Acad Radiol, 7(3):149-155. 13. Kansal AR, Torquato S, Harsh GI, Chiocca EA, Deisboeck TS (2000) Simulated brain tumor growth dynamics using a three-dimensional cellular automaton. J Theor Biol, 203(4):367-382