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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 (ST) measures gene expression at fine-grained spatial resolution, offering insights into tissue molecular landscapes. Previous methods for spatial gene expression prediction typically crop spots of interest from…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Ruikun Zhang , Yan Yang , Liyuan Pan

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

The spatial location of cells within tissues and organs is crucial for the manifestation of their specific functions.Spatial transcriptomics technology enables comprehensive measurement of the gene expression patterns in tissues while…

Quantitative Methods · Quantitative Biology 2024-07-12 Shuailin Xue , Fangfang Zhu , Changmiao Wang , Wenwen Min

Spatial transcriptomics (ST) maps gene expression within tissue at individual spots, making it a valuable resource for multimodal representation learning. Additionally, ST inherently contains rich hierarchical information both across and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Xulin Chen , Junzhou Huang

Single-cell transcriptomics and proteomics have become a great source for data-driven insights into biology, enabling the use of advanced deep learning methods to understand cellular heterogeneity and gene expression at the single-cell…

Genomics · Quantitative Biology 2025-12-15 Hiren Madhu , João Felipe Rocha , Tinglin Huang , Siddharth Viswanath , Smita Krishnaswamy , Rex Ying

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) 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 advances in multi-modal AI have demonstrated promising potential for generating the currently expensive spatial transcriptomics (ST) data directly from routine histology images, offering a means to reduce the high cost and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Junchao Zhu , Ruining Deng , Junlin Guo , Tianyuan Yao , Juming Xiong , Chongyu Qu , Mengmeng Yin , Yu Wang , Shilin Zhao , Haichun Yang , Daguang Xu , Yucheng Tang , Yuankai Huo

Spatial transcriptomics is a modern sequencing technology that allows the measurement of the activity of thousands of genes in a tissue sample and map where the activity is occurring. This technology has enabled the study of the so-called…

Methodology · Statistics 2022-09-15 Andrea Sottosanti , Davide Risso

Deep learning-based nuclei segmentation and classification in pathology images typically rely on large-scale pixel-level manual annotations, which are costly and difficult to obtain across diverse tissues and staining conditions. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Kazuya Nishimura , Ryoma Bise , Haruka Hirose , Yasuhiro Kojima

Spatial transcriptomics (ST) technologies enable transcriptome-wide gene expression profiling while preserving spatial resolution, offering unprecedented opportunities to uncover complex spatial structures. Due to the ultra-high…

Applications · Statistics 2026-03-11 Changhu Wang , Qiyun Huang , Zihao Chen , Jin Liu , Ruibin Xi

Spatial transcriptomics (ST) has revolutionized biomedical research by enabling high resolution gene expression profiling within tissues. However, the high cost and scarcity of high resolution ST data remain significant challenges. We…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Yaoyu Fang , Jiahe Qian , Xinkun Wang , Lee A. Cooper , Bo Zhou

Predicting spatial gene expression from H&E histology offers a scalable and clinically accessible alternative to sequencing, but realizing clinical impact requires models that generalize across cancer types and capture biologically coherent…

Machine Learning · Computer Science 2026-02-10 Susu Hu , Qinghe Zeng , Nithya Bhasker , Jakob Nikolas Kather , Stefanie Speidel

Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-increasing resolution and sensitivity. However, costs, rapidly evolving technology, and lack of standards have constrained computational methods in…

Histology imaging is an important tool in medical diagnosis and research, enabling the examination of tissue structure and composition at the microscopic level. Understanding the underlying molecular mechanisms of tissue architecture is…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Ronald Xie , Kuan Pang , Sai W. Chung , Catia T. Perciani , Sonya A. MacParland , Bo Wang , Gary D. Bader

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) 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

The rapid development of spatial transcriptomics (ST) offers new opportunities to explore the gene expression patterns within the spatial microenvironment. Current research integrates pathological images to infer gene expression, addressing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Junchao Zhu , Ruining Deng , Tianyuan Yao , Juming Xiong , Chongyu Qu , Junlin Guo , Siqi Lu , Yucheng Tang , Daguang Xu , Mengmeng Yin , Yu Wang , Shilin Zhao , Yaohong Wang , Haichun Yang , Yuankai Huo

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