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020 _a9783540356271
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024 7 _a10.1007/11783237
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082 0 4 _a006.37
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245 1 0 _aDigital Mammography
_h[electronic resource] :
_b8th International Workshop, IWDM 2006, Manchester, UK, June 18-21, 2006, Proceedings /
_cedited by Susan M. Astley, Michael Brady, Chris Rose, Reyer Zwiggelaar.
250 _a1st ed. 2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2006.
300 _aXVI, 654 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v4046
505 0 _aBreast Density -- CAD -- Clinical Practice -- Tomosynthesis -- Registration and Multiple View Mammography -- Physics Models -- Poster Session -- Wavelet Methods -- Full-Field Digital Mammography -- Segmentation.
520 _aThis volume of Springer’s Lecture Notes in Computer Science series records th the proceedings of the 8 International Workshop on Digital Mammography (IWDM), which was held in Manchester, UK, June 18–21, 2006. The meetings bringtogetheradiversesetofresearchers(physicists,mathematicians,computer scientists, engineers), clinicians (radiologists, surgeons) and representatives of industry, who are jointly committed to developing technology, not just for its ownsake,but to supportclinicians inthe earlydetection andsubsequentpatient management of breast cancer. The conference series was initiated at a 1993 meeting of the SPIE in San Jose, with subsequent meetings hosted every two years by researchers around the world. Previous meetings were held in York, Chicago, Nijmegen, Toronto, Bremen, and North Carolina. It is interesting to re?ect on the changes that have occurred during the past 13 years. Then, the dominant technology was ?lm-screen mammography; now it is full-?eld digital mammography. Then, there were few screening programmes world-wide; now there are many. Then, there was the hope that computer-aided detection (CAD) of early signs of cancer might be possible; now CAD is not only a reality but (more importantly) a commercially led clinical reality. Then, algorithmswerealmostentirelyheuristicwithlittleclinicalsupport;nowthereis arequirementforsubstantialclinicalsupportforanyalgorithmthatisdeveloped and published. However, upon re?ection, could we have predicted with absolute certainty what would be the key questions to be addressed over the subsequent (say) six years? No! That is the nature, joy, and frustration of research. There are more blind alleys to explore than there are rich veins that bring gold (in all senses of that analogy!).
650 0 _aComputer vision.
650 0 _aMedical informatics.
650 0 _aRadiology.
650 0 _aInformation storage and retrieval systems.
650 0 _aPattern recognition systems.
650 0 _aBioinformatics.
650 1 4 _aComputer Vision.
650 2 4 _aHealth Informatics.
650 2 4 _aRadiology.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aAutomated Pattern Recognition.
650 2 4 _aBioinformatics.
700 1 _aAstley, Susan M.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aBrady, Michael.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aRose, Chris.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aZwiggelaar, Reyer.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540356257
776 0 8 _iPrinted edition:
_z9783540825944
830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v4046
856 4 0 _uhttps://doi.org/10.1007/11783237
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