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SUMMARY:Mathematical Image Analysis for Cancer Research - Joana Grah\, DAM
 TP
DTSTART:20150128T140000Z
DTEND:20150128T150000Z
UID:TALK57711@talks.cam.ac.uk
CONTACT:38916
DESCRIPTION:Research in biomedical sciences is increasingly relying on dig
 ital images. At the same time\, technical equipment for data acquisition a
 nd storage media are developing rapidly\, raising an urgent need for suita
 ble image enhancement and processing techniques. In mathematical imaging a
  vast variety of different models and methods exists to track cells with f
 luorescence markers. However\, this technique has some disadvantages\, esp
 ecially the staining often causing cell death. Consequently\, live-cell im
 aging\, in particular observation of mitotic events\, is very difficult or
  even impossible. In contrast to fluorescence microscopy\, phase contrast 
 microscopy yields many advantages and facilitates live-cell imaging experi
 ments since staining is avoided. One specific problem we would like to add
 ress in this talk is the development of tools for automatic mitosis detect
 ion and tracking of cancer cells. Time-lapse observations of cell division
 s are a measurement to determine the percentage of cells undergoing mitosi
 s (mitotic index analysis). The mitotic index is an important prognostic f
 actor predicting both overall survival and response to chemotherapy in mos
 t types of cancer. Durations of the cell cycle and mitosis vary in differe
 nt cell types. An elevated mitotic index indicates more cells are dividing
 \, and thus is one of the key measurements in cancer drug development stud
 ies.
LOCATION:MR4\, Centre for Mathematical Sciences\, Wilberforce Road\, Cambr
 idge
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