Comparison based on sub-images segmentation accuracy in terms of percentage.

<p>Comparison based on sub-images segmentation accuracy in terms of percentage.</p>

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Bibliographic Details
Main Author:	Faqir Gul (20760068) (author)
Other Authors:	Mohsin Shah (3144564) (author), Mushtaq Ali (3598514) (author), Lal Hussain (14100502) (author), Touseef Sadiq (20175797) (author), Adeel Ahmed Abbasi (20760071) (author), Mohammad Shahbaz Khan (17140693) (author), Badr S. Alkahtani (20760074) (author)
Published:	2025
Subjects:	Biochemistry Medicine Cell Biology Biotechnology Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified publicly available datasets performs efficient segmentation g ., x including imageclefmed 2013 image type identification facilitates fast retrieval panel image types irregular image layouts xlink "> multi significantly enhances sub represent approximately 50 patient &# 8217 novel hybrid framework panel images play irregular medical images panel image image retrieval irregular multi proposed framework imageclefmed 2016 hybrid multi consolidated image medical images medical literature medical diagnostics images serve various multi thorough representation paper presents morphological operations important tools extracting sub essential role ct scans consolidated multi component sub achieving accurate
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