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PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20230312T030000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
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DTSTART:20231105T010000
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BEGIN:VEVENT
DTSTAMP:20230904T120316Z
UID:441D2555-E84E-49A8-952C-3E07547FC3F2
DTSTART;TZID=America/New_York:20230901T093000
DTEND;TZID=America/New_York:20230901T103500
DESCRIPTION:Medical ultrasound imaging is widely used for the diagnosis of 
 various diseases because of its noninvasiveness and real-time performance.
  However\, due to the ultrasound-specific phenomena\, it is difficult to u
 nderstand what is visualized on ultrasound images without the knowledge an
 d experience of the examiner. To overcome this difficulty\, many quantific
 ation techniques have been developed. This presentation will outline the f
 actors that make ultrasound images difficult to understand. I will then de
 scribe our recent work to quantify and visualize liver diseases based on t
 he statistics-based analysis of ultrasound echo signals.\n\nCo-sponsored b
 y: CU@EMBS\n\nSpeaker(s): Dr. Shohei Mori\, \n\nRoom: 3101\, Bldg: Canal B
 uilding\, Carleton University\, 11 Colonel By Drive\, Ottawa\, Ontario\, C
 anada\, K1S5B6
LOCATION:Room: 3101\, Bldg: Canal Building\, Carleton University\, 11 Colon
 el By Drive\, Ottawa\, Ontario\, Canada\, K1S5B6
ORGANIZER:sreeramanr@sce.carleton.ca
SEQUENCE:10
SUMMARY:Medical ultrasound imaging: quantification and visualization of dis
 eases
URL;VALUE=URI:https://events.vtools.ieee.org/m/371577
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;Medical ultrasound imaging is widely used 
 for the diagnosis of various diseases because of its noninvasiveness and r
 eal-time performance. However\, due to the ultrasound-specific phenomena\,
  it is difficult to understand what is visualized on ultrasound images wit
 hout the knowledge and experience of the examiner. To overcome this diffic
 ulty\, many quantification techniques have been developed. This presentati
 on will outline the factors that make ultrasound images difficult to under
 stand. I will then describe our recent work to quantify and visualize live
 r diseases based on the statistics-based analysis of ultrasound echo signa
 ls.&lt;/p&gt;
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