Tootfinder

Flatten Wisely: How Patch Order Shapes Mamba-Powered Vision for MRI Segmentation
Osama Hardan, Omar Elshenhabi, Tamer Khattab, Mohamed Mabrok
https://arxiv.org/abs/2507.13384

Flatten Wisely: How Patch Order Shapes Mamba-Powered Vision for MRI Segmentation
Vision Mamba models promise transformer-level performance at linear computational cost, but their reliance on serializing 2D images into 1D sequences introduces a critical, yet overlooked, design choice: the patch scan order. In medical imaging, where modalities like brain MRI contain strong anatomical priors, this choice is non-trivial. This paper presents the first systematic study of how scan order impacts MRI segmentation. We introduce Multi-Scan 2D (MS2D), a parameter-free module for Mamba…

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
Giuseppe Di Caro, Vahagn Kirakosyan, Alexander G. Abanov, Luca Candelori, Nadine Hartmann, Ernest T. Lam, Kharen Musaelian, Ryan Samson, Dario Villani, Martin T. Wells, Richard J. Wenstrup, Mengjia Xu
https://arxiv.org/abs/2506.03199

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
The accurate prediction of chromosomal instability from the morphology of circulating tumor cells (CTCs) enables real-time detection of CTCs with high metastatic potential in the context of liquid biopsy diagnostics. However, it presents a significant challenge due to the high dimensionality and complexity of single-cell digital pathology data. Here, we introduce the application of Quantum Cognition Machine Learning (QCML), a quantum-inspired computational framework, to estimate morphology-pred…

A System for Accurate Tracking and Video Recordings of Rodent Eye Movements using Convolutional Neural Networks for Biomedical Image Segmentation
Isha Puri, David Cox
https://arxiv.org/abs/2506.08183

A System for Accurate Tracking and Video Recordings of Rodent Eye Movements using Convolutional Neural Networks for Biomedical Image Segmentation
Research in neuroscience and vision science relies heavily on careful measurements of animal subject's gaze direction. Rodents are the most widely studied animal subjects for such research because of their economic advantage and hardiness. Recently, video based eye trackers that use image processing techniques have become a popular option for gaze tracking because they are easy to use and are completely noninvasive. Although significant progress has been made in improving the accuracy and robus…