TN-Mammo: A Curated Multi-View Mammography Dataset with Consensus Radiologist Annotations for Breast Density Stratification in a Vietnamese Cohort

المؤلفون

  • Hanan Alsagheer Amir EL-sseid Statistical Analysis Department, Faculty of Applied Science, Sebha University, Sabha, Libya المؤلف
  • Fatah Mohamed Shakrum High Institute of Medical Technology Abo salim, Tripoli, Libya المؤلف
  • Ebtisam Mohamed Fakroun Information Technology, The College Of Industrial Technology, Mısrata, Libya المؤلف
  • Mohamed EL-sseid Department of Software Engineering, Ankara Bilim University, Türkiye المؤلف
  • Abdussalam Ali Ahmed Mechanical and Industrial Engineering Department, Bani Waleed University, Libya المؤلف
  • Yasser Fathi Nassar Wadi Alshatti University, Brack, Libya, Libya المؤلف
  • Abdulgader Alsharif Department of Electric and Electronic Engineering, College of Technical Sciences Sebha, Libya المؤلف

DOI:

https://doi.org/10.65405/t18s9k62

الكلمات المفتاحية:

مجموعة بيانات تصوير الثدي الشعاعي، تصنيف كثافة الثدي، BI-RADS، التصوير متعدد المشاهد، توافق آراء أخصائيي الأشعة، مجموعة فيتنامية، شرح الصور الطبية، تنسيق البيانات الجاهزة للذكاء الاصطناعي

الملخص

لا يزال التصوير الشعاعي الرقمي للثدي الطريقة الرئيسية لفحص السكان، ولا يزال الكشف المبكر عن سرطان الثدي ضروريًا للإدارة السريرية الناجحة. وقد أظهرت الأساليب الحسابية الحديثة، وخاصة تلك التي تستخدم بنى التعلم العميق، إمكانات واعدة في تحسين التقييم الإشعاعي؛ ومع ذلك، فإن تمثيلية ودقة بيانات التدريب الأساسية تحدّ بطبيعتها من فعاليتها. وتعاني مجموعات بيانات التصوير الشعاعي للثدي العامة الحالية أحيانًا من مشكلات تتعلق باكتمال الصور متعددة الزوايا، أو عمليات التوصيف، أو التنوع الديموغرافي، مما يحد من إمكانية تعميمها على سياقات سريرية متنوعة. وقد مثّل هذا البحث مجموعة بيانات TN-Mammo، وهي مجموعة بيانات مختارة بعناية للتصوير الشعاعي للثدي متعدد الزوايا من مجموعة مرضى فيتناميين، لسدّ هذه الثغرات. وقد ساهمت كل مشاركة بصور متطابقة تشريحيًا للثديين الأيمن والأيسر في المكتبة، والتي تتضمن إسقاطات ثنائية من أعلى إلى أسفل (CC) ومن الجانب إلى الجانب (MLO) لـ 676 فردًا. وقام اثنان من أخصائيي الأشعة المعتمدين بتقييم تصنيف كثافة الثدي بشكل منفصل، وهو مؤشر حاسم لتصنيف مخاطر الإصابة بالسرطان، باستخدام منهجية مزدوجة التعمية. استُخدمت عملية التحكيم التوافقي لتحديد التصنيفات النهائية. ولضمان التوافق السريري، تلتزم تصنيفات الكثافة بإطار عمل BI-RADS ذي المستويات الأربعة (الفئات من أ إلى د). يصف هذا البحث عملية جمع البيانات، وتقنية الشرح، ومقاييس الاتفاق بين المُشاهدين، والخصائص الإحصائية الأساسية لمجموعة البيانات. يهدف هذا البحث إلى المساهمة في تطوير أنظمة ذكاء اصطناعي عادلة ومراعية لاحتياجات السكان لفحص سرطان الثدي في المناطق الأقل تمثيلاً، وتمكين إجراء بحوث قابلة للتكرار في التشخيص بمساعدة الحاسوب مع مراعاة الكثافة، وذلك من خلال إتاحة بيانات TN-Mammo للجمهور عبر PhysioNet.

التنزيلات

تنزيل البيانات ليس متاحًا بعد.

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التنزيلات

منشور

2025-12-06

كيفية الاقتباس

TN-Mammo: A Curated Multi-View Mammography Dataset with Consensus Radiologist Annotations for Breast Density Stratification in a Vietnamese Cohort. (2025). مجلة العلوم الشاملة, 10(38), 2065-2083. https://doi.org/10.65405/t18s9k62

الأعمال الأكثر قراءة لنفس المؤلف/المؤلفين