Detection and Classification for Blood Cancer – A Survey

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-36 Number-2
Year of Publication : 2016
Authors : Kuntal Barua, Prasun Chakrabarti
  10.14445/22312803/IJCTT-V36P111

MLA

Kuntal Barua, Prasun Chakrabarti "Detection and Classification for Blood Cancer – A Survey". International Journal of Computer Trends and Technology (IJCTT) V36(2):65-70, June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The paper entailsan idea to develop an automated method of analysis of AML blast cell images and to include in image-processing software, which enables the haematologist to diagnose AML more effectively and efficiently. Haematologists often face difficulties identifying the subtypes of AML, due to the similarities of their morphological features. Following AML detection, blast cells need to be classified into M3 or one of the other subtypes. The reason for targeting M3 is that its treatment differs from the treatment of the rest, requiring All- Trans-Retinoic-Acid (ATRA) to be added to the initial chemotherapy.

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Keywords
Blood cancer, ALL, AML, CML, Haematologist.