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Spatial transcriptomics (ST) is essential for understanding diseases and developing novel treatments. It measures gene expression of each fine-grained area (i.e., different windows) in the tissue slide with low throughput. This paper…

Computer Vision and Pattern Recognition · Computer Science 2022-11-01 Yan Yang , Md Zakir Hossain , Eric A Stone , Shafin Rahman

Spatial transcriptomics (ST) provides essential spatial context by mapping gene expression within tissue, enabling detailed study of cellular heterogeneity and tissue organization. However, aligning ST data with histology images poses…

Spatial Transcriptomics (ST) profiles thousands of gene expression values at discrete spots with precise coordinates on tissue sections, preserving spatial context essential for clinical and pathological studies. With rising sequencing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yishun Zhu , Jiaxin Qi , Jian Wang , Yuhua Zheng , Jianqiang Huang

Spatial transcriptomics (ST) provides crucial insights into tissue micro-environments, but is limited to its high cost and complexity. As an alternative, predicting gene expression from pathology whole slide images (WSI) is gaining…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Mingcheng Qu , Yuncong Wu , Donglin Di , Yue Gao , Tonghua Su , Yang Song , Lei Fan

Spatial transcriptomics aims to connect high-resolution histology images with spatially resolved gene expression. To achieve better performance on downstream tasks such as gene expression prediction, large-scale pre-training is required to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Jiahe Qian , Yaoyu Fang , Ziqiao Weng , Xinkun Wang , Lee A. Cooper , Bo Zhou

Spatial transcriptomics (ST) has emerged as a powerful technology for bridging histology imaging with gene expression profiling. However, its application has been limited by low throughput and the need for specialized experimental…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Tinglin Huang , Tianyu Liu , Mehrtash Babadi , Wengong Jin , Rex Ying

Spatial transcriptomics (ST) has emerged as an advanced technology that provides spatial context to gene expression. Recently, deep learning-based methods have shown the capability to predict gene expression from WSI data using ST data.…

Machine Learning · Computer Science 2024-12-10 Mingcheng Qu , Yuncong Wu , Donglin Di , Anyang Su , Tonghua Su , Yang Song , Lei Fan

Spatial transcriptomics (ST) is a novel technology that enables the observation of gene expression at the resolution of individual spots within pathological tissues. ST quantifies the expression of tens of thousands of genes in a tissue…

Machine Learning · Computer Science 2025-11-25 Kaito Shiku , Kazuya Nishimura , Shinnosuke Matsuo , Yasuhiro Kojima , Ryoma Bise

Spatial transcriptomics (ST) is a novel technique that simultaneously captures pathological images and gene expression profiling with spatial coordinates. Since ST is closely related to pathological features such as disease subtypes, it may…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Kazuya Nishimura , Ryoma Bise , Yasuhiro Kojima

Spatial Transcriptomics is a novel technology that aligns histology images with spatially resolved gene expression profiles. Although groundbreaking, it struggles with gene capture yielding high corruption in acquired data. Given potential…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Gabriel Mejia , Daniela Ruiz , Paula Cárdenas , Leonardo Manrique , Daniela Vega , Pablo Arbeláez

Spatial Transcriptomics (ST) offers spatially resolved gene expression but remains costly. Predicting expression directly from widely available Hematoxylin and Eosin (H&E) stained images presents a cost-effective alternative. However, most…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Jiarui Ouyang , Yihui Wang , Yihang Gao , Yingxue Xu , Shu Yang , Hao Chen

Spatial transcriptomics (ST) provides spatially resolved measurements of gene expression, enabling characterization of the molecular landscape of human tissue beyond histological assessment as well as localized readouts that can be aligned…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Konstantin Hemker , Andrew H. Song , Cristina Almagro-Pérez , Guillaume Jaume , Sophia J. Wagner , Anurag Vaidya , Nikola Simidjievski , Mateja Jamnik , Faisal Mahmood

Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling of histopathology, providing valuable insights into…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Junzhuo Liu , Markus Eckstein , Zhixiang Wang , Friedrich Feuerhake , Dorit Merhof

Spatial transcriptomics offers spatially resolved gene expression profiling within tissue sections, but its cost and limited throughput hinder large-scale deployment. To extend this capability to routine practice, recent computational…

Machine Learning · Computer Science 2026-05-07 Keunho Byeon , Jin Tae Kwak

Spatially resolved transcriptomics (ST) measures gene expression along with the spatial coordinates of the measurements. The analysis of ST data involves significant computation complexity. In this work, we propose gene expression…

Genomics · Quantitative Biology 2022-05-24 Zhuoyan Xu , Kris Sankaran

Spatial transcriptomics is an emerging technology that aligns histopathology images with spatially resolved gene expression profiling. It holds the potential for understanding many diseases but faces significant bottlenecks such as…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Gabriel Mejia , Paula Cárdenas , Daniela Ruiz , Angela Castillo , Pablo Arbeláez

Spatial Transcriptomics (ST) reveals the spatial distribution of gene expression in tissues, offering critical insights into biological processes and disease mechanisms. However, the high cost, limited coverage, and technical complexity of…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Yi Niu , Jiashuai Liu , Yingkang Zhan , Jiangbo Shi , Di Zhang , Marika Reinius , Ines Machado , Mireia Crispin-Ortuzar , Jialun Wu , Chen Li , Zeyu Gao

The rapid development of spatial transcriptomics (ST) technologies is revolutionizing our understanding of the spatial organization of biological tissues. Current ST methods, categorized into next-generation sequencing-based (seq-based) and…

Machine Learning · Computer Science 2024-07-19 Xiaoyu Li , Fangfang Zhu , Wenwen Min

Spatial transcriptomics (ST) provides high-resolution pathological images and whole-transcriptomic expression profiles at individual spots across whole-slide scales. This setting makes it an ideal data source to develop multimodal…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Yuxiang Lin , Ling Luo , Ying Chen , Xushi Zhang , Zihui Wang , Wenxian Yang , Mengsha Tong , Rongshan Yu

Recent advancements in Spatial Transcriptomics (ST) technology have facilitated detailed gene expression analysis within tissue contexts. However, the high costs and methodological limitations of ST necessitate a more robust predictive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Youngmin Chung , Ji Hun Ha , Kyeong Chan Im , Joo Sang Lee
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