Geometric Feature Extraction for Identification and Classification of Overlapping Cells for Leukaemia
This paper is inte nded to assess [he feature ex trac lion te chnique for identificatIOn and c lassificatIon of whi le blood ce ll uue to ove rl app ing cond iti on in ieuka CI11IJ d isease. Accordi ng to the dala from SEER Cancer Stat istic s [ 1), leukaemia IS ont ofrhe lOp ten most common type...
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| Main Authors: | , |
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| Format: | Proceeding |
| Language: | en |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/26738/1/Geometric%20Feature.pdf http://ir.unimas.my/id/eprint/26738/ |
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| Summary: | This paper is inte nded to assess [he feature ex trac lion te chnique for identificatIOn
and c lassificatIon of whi le blood ce ll uue to ove rl app ing cond iti on in ieuka CI11IJ d isease.
Accordi ng to the dala from SEER Cancer Stat istic s [ 1), leukaemia IS ont ofrhe lOp ten
most common type s of blood ca ncer. In lhe year 20 17, there are {)2 130 peopl e are
expec ted to be diagnosed and 24500 peop le 3re expected to di e. In ano ther word,
app roxi mately (he re are I pe rso n is diagn osed with a bl ood ca ncer in every 3 minutes.
Th esc da la have shown how hi gh the risk of le ukaemia to be d iagno sed. Therefore, an
accurate Image process ing approa ch is proposed for cha gnosis leu k.tlcmia. |
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