صورة الغلاف

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring

: Experts have used ultrasound imaging to manually determine follicle count and perform measurements, especially in cases of polycystic ovary syndrome (PCOS). However, due to the laborious and error-prone process of manual diagnosis, researchers have explored and developed medical image processing...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Nazarudin, Asma’ Amirah, Zulkarnain, Noraishikin, Mokri, Siti Salasiah, Wan Zaki, Wan Mimi Diyana, Hussain, Aini, Ahmad, Mohd Faizal, Mohd Nordin, Najaa Aimi
التنسيق:	مقال
اللغة:	English
منشور في:	Mdpi 2023
الموضوعات:	T Technology (General)
الوصول للمادة أونلاين:	http://eprints.uthm.edu.my/10290/1/J15891_a3d347f8edddeb01c372c95d56a57036.pdf http://eprints.uthm.edu.my/10290/ https://doi.org/10.3390/diagnostics13040750
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring
بواسطة: Nazarudin, Asma’ Amirah, وآخرون
منشور في: (2023)

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring
بواسطة: Nazarudin, Asma’ Amirah, وآخرون
منشور في: (2023)

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring
بواسطة: Nazarudin, Asma’ Amirah, وآخرون
منشور في: (2023)

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring
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منشور في: (2023)

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring
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