In‐situ observations of spatial variations of the wave‐particle interaction region require a large number of satellite probes. As an alternative, flash‐type auroras, a kind of pulsating aurora, driven by discrete chorus elements, can be used to investigate the interaction region with a high spatial resolution. We estimated the spatial extent of wave‐particle interaction region from ground‐based observations of flash aurora at Gakona (62.39°N, 214.78°E), Alaska at subauroral latitudes, and found that the auroral expansion was predominantly to the low‐latitude side. The spatial displacement is thought to be caused by the propagation effects of chorus waves in the magnetosphere. Using ray tracing analysis to take into account chorus wave propagation, we reconstructed the spatiotemporal evolution of the volume emission rate and confirmed that the predominant expansion is toward the lower‐latitude side in the ionosphere. This study shows that chorus wave propagation in the magnetosphere gives new insight for characterizing the transverse size (across the geomagnetic field line) of wave‐particle interaction regions. The calculated spatial scale of the column auroral emission shows a correlation with the magnetic latitude of the resonance region at magnetic latitudes within 10° of the equatorial plane of the magnetosphere. Our results suggest that the spatial scale of a flash aurora is indirectly related to the chorus amplitude because the latitudinal range of the wave‐particle interaction is important for the growth of wave amplitude.

Optical flow estimation is a fundamental and long-standing task in computer vision, facilitating the understanding of motion within visual scenes. In this study, we aim to improve optical flow estimation, particularly in challenging scenarios involving small and fast-moving objects. Specifically, we proposed a learning-based model incorporating two key components: the Hierarchical Motion Field Alignment module, which ensures accurate estimation of objects of varying sizes while maintaining manageable computational complexity, and the Correlation Self-Attention module, which effectively handles large displacements, making the model suitable for scenarios with fast-moving objects. Additionally, we introduced a Multi-Scale Correlation Search layer to enhance the four-dimensional cost volume, enabling the model to address various types of motion. Experimental results demonstrate that our model achieves superior generalization performance and significantly improves the estimation of small, fast-moving objects.

Objective interpretation of myocardial ^99mTc-pyrophosphate (PYP) uptake is important in suspected cardiac amyloidosis. We developed a segmentation-informed multimodal framework that classifies myocardial PYP uptake from planar and single-photon emission computed tomography (SPECT) images. The retrospective, class-enriched cohort comprised 49 studies from 44 patients (19 PYP-positive and 25 PYP-negative) with specialist-confirmed image labels. Five consecutive SPECT slices were manually selected under nuclear-medicine-physician supervision; subsequent processing was automated. SPECT Net generated an unthresholded myocardial probability map, which served as a soft, spatially interpretable representation for integration with planar features. Patient-grouped five-fold cross-validation used separate validation and test folds. In PYP-positive patients, cropped nnU-Net achieved a patient-level Dice coefficient of $0.9209\pm 0.0316$ and outperformed three segmentation comparators after Holm correction ($p<0.001$). Transformer-style fusion achieved 95.5% accuracy (95% confidence interval: 84.9–98.7%), 89.5% sensitivity, 100.0% specificity, and a 94.4% F1-score. Improvements over planar-only classification (90.9%; McNemar $p=0.500$), localized raw SPECT (86.4%; $p=0.125$), and H/CL assessment (88.6%; $p=0.250$) were not significant. These single-center internal results demonstrate the feasibility of using a soft myocardial segmentation output as an interpretable bridge for multimodal PYP uptake classification but do not establish superiority; multicenter external validation is required.