Fractal-Based Architectures with Skip Connections and Attention Mechanism for Improved Segmentation of MS Lesions in Cervical Spinal Cord.

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

Who cites it

3 citing papers in PubMed.

1. Fully Automated Segmentation of Cervical Spinal Cord in Sagittal MR Images Using Swin-Unet Architectures.Journal of clinical medicine · 2025
   Article
2. MAF-net: multi-receptive attention fusion network with dual-path squeeze-and-excitation enhancement module for uterine fibroid segmentation.Frontiers in physiology · 2025
   Article
3. Applications, image analysis, and interpretation of computer vision in medical imaging.Frontiers in radiology · 2025
   Review

Corrections and comments

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Authors and funding

3 authors.

Funding

Abstract

PubMed holds no abstract for this paper.

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