17 papers · ranked by Valyu relevance
A. Murat Maga, Jean-Christophe Fillion-Robin
The digitization of biological specimens has revolutionized the field of morphology, creating large collections of 3D data, and microCT in particular. This revolution was initially supported by the development of open-source software tools, specifically the development of SlicerMorph extension to the open-source image…
A. Murat Maga, Jean-Christophe Fillion-Robin
The digitization of biological specimens has revolutionized the field of morphology, creating large collections of 3D data, and microCT in particular. This revolution was initially supported by the development of open-source software tools, specifically the development of SlicerMorph extension to the open-source image…
Erick Oliveira Rodrigues, Aura Conci
This work introduces mathematical morphology-an established visual computing theory-into machine learning to exploit shape and density aspects often overlooked by standard techniques. We propose a fast clustering algorithm based on morphological reconstruction that accurately preserves cluster shapes and density. This…
Chuan-Shen Hu
Dr. Chuan-Shen Hu received his Ph.D. in Mathematics from National Taiwan Normal University (NTNU), Taiwan, in 2022. He subsequently held postdoctoral fellow positions at the School of Physical and Mathematical Sciences (SPMS), Nanyang Technological University (NTU), Singapore, and at the Department of Mathematics…
Sebastian Magana, Wenjun Zhao, Khanh Dao Duc
Inferring continuous morphological transformations from collections of static biological snapshots is an important, yet challenging problem. In the context of cellular biology, prevailing approaches reduce 3D shape collections to static reconstructions or hand-crafted descriptors, which fail to capture smooth…
Shuo Wen, Ramon Viñas Torné, Johannes Bues, Camille Lucie Lambert + 8 more
The understanding of how transcriptional programs give rise to cellular morphology, and how morphological features reflect and influence cell identity and function remains limited. This is due in part to the lack of large-scale datasets pairing the two modalities as well as the absence of computational frameworks…
Yossi Bokor Bleile, Pooja Yadav, Patrice Koehl, Florian Rehfeldt + 1 more
Quantifying cell morphology is central to understanding cellular regulation, fate, and heterogeneity, yet conventional image-based analyses often struggle with diverse or irregular shapes. We present a computational framework that uses topological data analysis to characterise and compare single-cell morphologies from…
Xinhao Liu, Hongyu Zheng, Peter Halmos, Julian Gold + 3 more
Recent efforts to build comprehensive tissue and tumor atlases leverage diverse spatial technologies to measure transcriptomic, proteomic, epigenetic, and other modalities with hundreds to thousands of features at thousands to millions of spatially resolved locations in a tissue slice. Integrating such data across…
Taymaz Akan, Richa Aishwarya, Md. Shenuarin Bhuiyan, Mohammad Alfrad Nobel Bhuiyan
Tissue analysis is considered the gold standard for the diagnosis of a wide spectrum of disorders. However, pathologists perform labor-intensive evaluations to ensure accurate results. Computational pathology has made significant advances in the development of task-specific predictive models. Nevertheless, traditional…
Felix Y. Zhou, Zach Marin, Clarence Yapp, Qiongjing Zou + 15 more
Cell segmentation is the foundation of a wide range of microscopy-based biological studies. Deep learning has revolutionized two-dimensional (2D) cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation and…
Alex Khang, Mark W. Young, Dilara Batan, Kristi S. Anseth
As cell imaging grows in scale, precision, and complexity, data integration and harmonization become increasingly important for studying cell–material interactions. Quantitative understanding of how cells respond to mechanical cues, such as substrate stiffness and topography, is often limited by differences in…
Mari Tolonen, Ziwei Xu, Ozgur Beker, Varun Kapoor + 2 more
Cell state transitions underlie the emergence of diverse cell types and are traditionally defined by changes in gene expression. Yet these transitions also involve coordinated shifts in cell morphology and behavior, which remain poorly characterized in densely packed epithelia. We developed a quantitative live-imaging…
Killian Rigaux, André Ferreira Castro, Lida Kanari
Neuronal morphogenesis arises through coordinated neurite dynamics that generate cell-type specific dendritic branching during development. Recent advances in high-throughput time-lapse imaging techniques have transformed our ability to track such growth dynamics, yielding comprehensive anatomical datasets of neuronal…
Mercedes Quintana, Le Yang Loh, Ayush Parikh, Jonathan J. Suh + 4 more
Morphological measurements underpin a wide range of ecological and evolutionary research, yet the manual landmarking workflows on which most morphometric studies depend remain a persistent bottleneck that limits both the pace and scale of biological research. Machine learning offers compelling solutions, but most…
Wenxiao Li, Faqiang Wang, Yuping Duan, Li Cui + 2 more
Topological features play an essential role in ensuring geometric plausibility and structural consistency in image analysis tasks such as segmentation and skeletonization. However, integrating topology-preserving learning based on simple points into deep learning tasks remains challenging, as existing simple point…
Johannes Girstmair, Tobias Pietzsch, Vladimir Ulman, Stefan Hahmann + 7 more
Understanding development in living organisms requires following the divisions, movements, and fates of cells across developing systems. While advances in microscopy have enabled whole-embryo imaging at the cellular level, extracting and analyzing cell lineages from these massive datasets remains a significant…
Authors not listed
Assembly of block copolymers (BCPs) with epoxy is useful to enhance the mechanical toughness of 3D-printable epoxy inks. Recently, ionic liquids (ILs) like 1-Ethyl-3-Methylimidazolium dicyanamide ([EMIM][DCA]) have enhanced the self-assembly of pure BCP, enabling the formation of a controlled nanostructure. However…