The paper argues that internal self-consistency checks cannot guarantee the accuracy of photogrammetric reconstructions, a limitation that is structural rather than a tuning issue. It introduces a track‑leakage‑free hold‑out protocol that withholds a deterministic subset of images and tests each against only 3D points supported by at least two retained images, ensuring no view is evaluated against the structure it helped create. Experiments on diverse datasets show that while the protocol is well‑posed, it saturates at a confidence score of 1.00 and fails to detect coherent distortion, missing large errors that can reach over 100 m.
whyItMatters":"The study highlights that hold‑out self‑validation scores, increasingly used as quality evidence for metric deliverables, may be misleading and cannot replace external survey validation."
By Behnam Asadi
arXiv:2606. 15910v2 Announce Type: replace Abstract: A vision-language model can answer a question about a chest radiograph or a pathology slide fluently and confidently while barely using the image, relying instead on language priors.
By Reza Khanmohammadi, Kundan Thind, Mohammad M. Ghassemi
arXiv:2608.30143v1 Announce Type: new
Abstract: We characterise the measurement error of a free- hand consumer structured-light scanner used to derive three- dimensional geometric wound descriptors....
By Pushkal Kumar, Aadit Aggarwal, Karlen Aleksanyan
The paper introduces a decision‑aware evaluation protocol for medical image segmentation uncertainty that separates uncertainty estimation from deferral policy and assesses their joint performance under fixed review budgets. It reports metrics such as fixed‑budget error reduction, risk‑coverage behavior, region‑level review proxies, structural failure modes, and sensitivity to review assumptions. Experiments on retinal vessel, skin lesion, and polyp segmentation with various backbones and uncertainty estimators show that estimator rankings vary with review unit, uncertainty target, and cost model, and that boundary and thin‑structure failures are partly due to annotation ambiguity.
By Saket Maganti, Shreyank N Gowda
arXiv:2607. 13682v2 Announce Type: cross Abstract: Radiative Gaussian splatting reconstructs sparse-view CT fast and accurately, and recent work attaches per-Gaussian posteriors to yield per-voxel uncertainty maps.
By Chulin Zhao, Yiran Xu, Shu Liu
Progress in colonoscopy polyp segmentation is routinely reported through leaderboard comparisons on a small set of public benchmarks. We argue that this apparent progress is difficult to verify: a systematic audit of \textbf{27 papers} published between 2015 and 2026 reveals three structural problems in how the community evaluates models.
arXiv:2609.24725v1 Announce Type: cross
Abstract: Head-and-neck anatomy changes over a six-to-seven-week proton course, and the anatomy of a later week cannot be imaged when the plan is made. We pres...
By Yizhou Wu, Jie Ding, Justin Roper, Minglei Kang, Yuheng Li, Sibo Tian, David S. Yu, Xiaofeng Yang, Chih-Wei Chang
The paper audits a prenatal ultrasound biometry pipeline that predicts head circumference (HC) while certifying a maximum error rate rather than magnitude. Using two pre‑registered splits of 999 HC18 images, the authors retrain the segmenter three times per split and calibrate a contour‑completeness threshold via exact Clopper–Pearson risk control. Although the certified risk bound (α = 0.10) remains intact, the pipeline still produces a large 271.3 mm error on a single image, and tightening the admissibility region to an anatomically defined range reduces worst‑case errors to about 11 mm while only modestly affecting coverage.
By Zhengshuai Yang, Linna Jiang, Changyun Li, Guihu Zhao
Vision–language models can correctly diagnose medical questions using only the clinical vignette, without the diagnostic image. In experiments on 60 Italian State Examination items, models defended diagnoses derived from a blank placeholder as firmly as those derived from real images, showing no increased fragility. While different adversarial pressures produced distinct dynamics—one leading to a single decisive flip and the other to continual changes—the instability under contentless doubt reflected item ambiguity rather than lack of evidence.
By Federico Felizzi, Francesco Andrea Causio, Bianca Destro Castaniti, Olivia Riccomi, Michele Ferramola, Vittorio De Vita, Alessandro Tosi, Antonio Cristiano, Alessia Longo, Lorenzo De Mori, Chiara Battipaglia, Melissa Sawaya, Luigi De Angelis, Marcello Di Pumpo, Alessandra Piscitelli, Pietro Eric Risuleo, Giulia Vojvodic, Mariapia Vassalli, Nicolo Scarsi, Manuel Del Medico
The paper introduces Cros, a risk‑constrained stopping layer for sequential clinical diagnosis agents that determines when to stop testing and make a diagnosis. Cros combines state‑wise error ranking, policy design on disjoint development splits, and exact tests of selective diagnostic error to provide finite‑sample guarantees. On a MIMIC‑derived abdominal‑pain benchmark, Cros achieves higher state‑error AUROC and lower selective error rates compared to baseline stopping methods, though its performance varies across development resplits.
By Yuexin Wu, Vasile Rus
SpatialUQ is a post‑hoc uncertainty quantification method that uses only the output probabilities of frozen black‑box vision models. It computes the Jensen‑Shannon divergence between the global prediction and the mean of five fixed spatial crops across six deterministic forward passes, assuming that trustworthy predictions are spatially consistent. On the NIH ChestX‑ray14 dataset, SpatialUQ’s Multicrop Uncertainty Score (MUS) achieves a 0.784 failure‑detection AUC—significantly higher than MC‑Dropout—while also providing superior native calibration and improving further when fused with other uncertainty signals.
By Md Kawsher Mahbub, Milon Biswas, Mirza Niaz Morshed, Wei Yu
The paper introduces a certified abstention approach for image registration, distinguishing between recoverable and provably-unidentifiable regions in reference-perturbed sampled imaging. It establishes a resolution threshold that separates these regimes and provides a framework that exactly recovers identifiable areas while abstaining from unreliable ones, avoiding hallucinated structures. Experiments on scanning, rolling‑shutter, and cryo‑electron‑microscopy systems confirm that the method abstains where classical or learned estimators fabricate artifacts.
By Dinh Tuan Nguyen, Trong Nhan Nguyen, Vu Nguyen Minh Hung, Tien Minh Khoi Nguyen, Jaeyeop Choi, Sudip Mondal, Jae Sung Ahn, Junghwan Oh