الملخص
Dense vessel annotation in digital subtraction angiography (DSA) is labor-intensive, yet every unlabeled sequence records how contrast passes through the vessels. Semi-supervised methods take their targets from the current model, and generic self-supervised pretexts reconstruct static appearance, so this signal goes unused. We propose ConPro, a self-supervised pretraining scheme whose target is a contrast projection, the normalized drop of every pixel below its temporal median over the sequence. On DIAS and DSCA, with 10%, 20% and 50% of the training cases labeled, ConPro improves on training from scratch at every label fraction and is the best of the compared methods on DSCA at 20% and 50% labels. Controlled comparisons show that the gain comes from the target. A temporal-median target with the same input, loss and budget stays at scratch level, and using the projection directly instead of learning it, as an input channel or a pseudo-label, helps little or hurts. ConPro provides pretrained weights without changing the segmentation architecture, so it combines with semi-supervised training, and UniMatch, the strongest baseline, gains 0.5 to 2.0 Dice and 0.9 to 2.3 clDice at every label fraction when started from ConPro weights, reaching 75.4 Dice on DIAS and 81.3 on DSCA.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Guo, X., Wang, Y., Shu, L., Liu, Y., & Xu, M. (2026). ConPro: Contrast Projection Pretraining for Label-Efficient Vessel Segmentation in DSA Sequences. https://omanscience.com/ar/articles/conpro-contrast-projection-pretraining-for-label-efficient-vessel-segmentation-in-dsa-sequences
MLA 9
Guo, Xinge, et al. "ConPro: Contrast Projection Pretraining for Label-Efficient Vessel Segmentation in DSA Sequences." https://omanscience.com/ar/articles/conpro-contrast-projection-pretraining-for-label-efficient-vessel-segmentation-in-dsa-sequences.
شيكاغو (المؤلف–التاريخ)
Guo, Xinge, Yuanhao Wang, Liqi Shu, Yang Liu, and Min Xu. 2026. "ConPro: Contrast Projection Pretraining for Label-Efficient Vessel Segmentation in DSA Sequences." https://omanscience.com/ar/articles/conpro-contrast-projection-pretraining-for-label-efficient-vessel-segmentation-in-dsa-sequences.
هارفارد
Guo, X., Wang, Y., Shu, L., Liu, Y. and Xu, M. (2026) 'ConPro: Contrast Projection Pretraining for Label-Efficient Vessel Segmentation in DSA Sequences', Available at: https://omanscience.com/ar/articles/conpro-contrast-projection-pretraining-for-label-efficient-vessel-segmentation-in-dsa-sequences.
فانكوفر
Guo X, Wang Y, Shu L, Liu Y, Xu M. ConPro: Contrast Projection Pretraining for Label-Efficient Vessel Segmentation in DSA Sequences. https://omanscience.com/ar/articles/conpro-contrast-projection-pretraining-for-label-efficient-vessel-segmentation-in-dsa-sequences
IEEE
X. Guo, Y. Wang, L. Shu, Y. Liu, and M. Xu, "ConPro: Contrast Projection Pretraining for Label-Efficient Vessel Segmentation in DSA Sequences," https://omanscience.com/ar/articles/conpro-contrast-projection-pretraining-for-label-efficient-vessel-segmentation-in-dsa-sequences.