arXiv:2511.04171v1 Announce Type: new 
Abstract: Image registration refers to the process of spatially aligning two or more images by mapping them into a common coordinate system, so that corresponding anatomical or tissue structures are matched across images. In digital pathology, registration enables direct comparison and integration of information from different stains or imaging modalities, sup-porting applications such as biomarker analysis and tissue reconstruction. Accurate registration of images from different modalities is an essential step in digital pathology. In this study, we investigated how various color transformation techniques affect image registration between hematoxylin and eosin (H&E) stained images and non-linear multimodal images. We used a dataset of 20 tissue sample pairs, with each pair undergoing several preprocessing steps, including different color transformation (CycleGAN, Macenko, Reinhard, Vahadane), inversion, contrast adjustment, intensity normalization, and denoising. All images were registered using the VALIS registration method, which first applies rigid registration and then performs non-rigid registration in two steps on both low and high-resolution images. Registration performance was evaluated using the relative Target Registration Error (rTRE). We reported the median of median rTRE values (MMrTRE) and the average of median rTRE values (AMrTRE) for each method. In addition, we performed a custom point-based evaluation using ten manually selected key points. Registration was done separately for two scenarios, using either the original or inverted multimodal images. In both scenarios, CycleGAN color transformation achieved the lowest registration errors, while the other methods showed higher errors. These findings show that applying color transformation before registration improves alignment between images from different modalities and supports more reliable analysis in digital pathology.

تسلط دراسة حديثة حول تسجيل الصور في علم الأمراض الرقمي الضوء على أهمية تقنيات المعالجة المسبقة الدقيقة لمحاذاة الصور. هذه العملية حاسمة لأنها تسمح بمقارنة أفضل ودمج البيانات من طرق التصوير المختلفة، مما يمكن أن يعزز بشكل كبير تحليل العلامات الحيوية وجهود إعادة بناء الأنسجة. من خلال تحسين دقة تسجيل الصور، يمكن للباحثين الحصول على رؤى أعمق حول هياكل الأنسجة، مما يؤدي في النهاية إلى تقدم في التشخيص الطبي والعلاج.

Un estudio reciente sobre el registro de imágenes en patología digital destaca la importancia de las técnicas de preprocesamiento precisas para alinear imágenes. Este proceso es crucial, ya que permite una mejor comparación e integración de datos de varios métodos de imagen, lo que puede mejorar significativamente el análisis de biomarcadores y los esfuerzos de reconstrucción de tejidos. Al mejorar la precisión del registro de imágenes, los investigadores pueden obtener una comprensión más profunda de las estructuras tisulares, lo que lleva a avances en el diagnóstico y tratamiento médico.

Une étude récente sur l'enregistrement d'images en pathologie numérique souligne l'importance des techniques de prétraitement précises pour aligner les images. Ce processus est crucial car il permet une meilleure comparaison et intégration des données provenant de diverses méthodes d'imagerie, ce qui peut considérablement améliorer l'analyse des biomarqueurs et les efforts de reconstruction tissulaire. En améliorant la précision de l'enregistrement d'images, les chercheurs peuvent obtenir des informations plus approfondies sur les structures tissulaires, menant finalement à des avancées dans le diagnostic médical et le traitement.

A recent study on image registration in digital pathology highlights the importance of accurate preprocessing techniques for aligning images. This process is crucial as it allows for better comparison and integration of data from various imaging methods, which can significantly enhance biomarker analysis and tissue reconstruction efforts. By improving the accuracy of image registration, researchers can gain deeper insights into tissue structures, ultimately leading to advancements in medical diagnostics and treatment.

Systematic Evaluation of Preprocessing Techniques for Accurate Image Registration in Digital Pathology

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