eess.IV · 2026-06-27 · No. 36

Image and Video Processing, 2026-06-27.

2 new papers in eess.IV. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Enabling self-supervised learned primal dual with Noise2Inverse

    Antti Sällinen, Siiri Rautio, Santeri Kaupinmäki, Andreas Hauptmann

    eess.IV · cs.LG · math.OC

    X-ray computed tomography reconstruction is an ill-posed inverse problem, particularly in low-dose and sparse-angle settings where measurements are noisy and incomplete. While learned reconstruction methods such as the Learned Primal-Dual algorithm achieve strong performance, they typically rely on supervised training with access to ground-truth data, which is often unavailable in practice. In this work, we propose a self-supervised...

    arxiv.org/abs/2606.26991 · PDF

  2. 02

    MLFFM-SegDiff: A Multi-Level Feature Fusion Diffusion Model for Skin Lesion Segmentation

    Jingjun Gu, Chaojie Shen, Yifeng Cao, Wei Zhang, Yiliu Li, Aobo Fan

    eess.IV · cs.AI · cs.CV

    Skin lesion segmentation is a key task in computer-aided dermatological diagnosis, where accuracy directly impacts downstream analysis and disease classification. However, dermoscopic images are challenging due to blurred boundaries, low contrast, large shape variations, and artifacts such as hair and shadows. Recently, diffusion models have shown strong performance in medical image segmentation thanks to their progressive denoising and...

    arxiv.org/abs/2606.26712 · PDF

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