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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 spatially resolved gene expression profiles within intact tissue architecture, enabling molecular analysis in histological context. However, the high cost, limited throughput, and restricted data…

Machine Learning · Computer Science 2026-03-31 Yaoyu Fang , Jiahe Qian , Xinkun Wang , Lee A. Cooper , Bo Zhou

Spatial Transcriptomics (ST) allows a high-resolution measurement of RNA sequence abundance by systematically connecting cell morphology depicted in Hematoxylin and Eosin (H&E) stained histology images to spatially resolved gene…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Sichen Zhu , Yuchen Zhu , Molei Tao , Peng Qiu

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

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

Spatial transcriptomics (ST) captures gene expression within distinct regions (i.e., windows) of a tissue slide. Traditional supervised learning frameworks applied to model ST are constrained to predicting expression from slide image…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Yan Yang , Md Zakir Hossain , Xuesong Li , Shafin Rahman , Eric Stone

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) 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

Spatially resolved transcriptomics represents a significant advancement in single-cell analysis by offering both gene expression data and their corresponding physical locations. However, this high degree of spatial resolution entails a…

Genomics · Quantitative Biology 2024-03-19 Xiaoyu Li , Wenwen Min , Shunfang Wang , Changmiao Wang , Taosheng Xu

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

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 (ST) reveals spatial heterogeneity of gene expression, yet its resolution is limited by current platforms. Recent methods enhance resolution via H&E-stained histology, but three major challenges persist: (1)…

Image and Video Processing · Electrical Eng. & Systems 2025-08-12 Xuepeng Liu , Zheng Jiang , Pinan Zhu , Hanyu Liu , Chao Li

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

The rapid advancement of spatial transcriptomics (ST), i.e., spatial gene expressions, has made it possible to measure gene expression within original tissue, enabling us to discover molecular mechanisms. However, current ST platforms…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Xiaofei Wang , Stephen Price , Chao Li

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 groundbreaking genomic technology that enables spatial localization analysis of gene expression within tissue sections. However, it is significantly limited by high costs and sparse spatial resolution. An…

Image and Video Processing · Electrical Eng. & Systems 2024-07-31 Zhiceng Shi , Shuailin Xue , Fangfang Zhu , Wenwen Min

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 provides an unprecedented perspective for deciphering tissue spatial heterogeneity. However, high-resolution spatial transcriptomic technology remains constrained by limited gene coverage, technical complexity, and…

Biomolecules · Quantitative Biology 2026-05-19 Xinlei Huang , Weihao Dai , Zijun Qin , Xin Yu , Di Wang , Yanran Liu , Lixin Cheng , Xubin Zheng

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 is a groundbreaking technology that integrates histology images with spatially resolved gene expression profiles. Among the various Spatial Transcriptomics techniques available, Visium has emerged as the most widely…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Daniela Ruiz , Paula Cárdenas , Leonardo Manrique , Daniela Vega , Gabriel M. Mejia , Pablo Arbeláez
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