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Timely and accurate lymphoma diagnosis is essential for guiding cancer treatment. Standard diagnostic practice combines hematoxylin and eosin (HE)-stained whole slide images with immunohistochemistry, flow cytometry, and molecular genetic…

Performance of data-driven network for tumor classification varies with stain-style of histopathological images. This article proposes the stain-style transfer (SST) model based on conditional generative adversarial networks (GANs) which is…

计算机视觉与模式识别 · 计算机科学 2018-12-21 Hyungjoo Cho , Sungbin Lim , Gunho Choi , Hyunseok Min

While machine learning is currently transforming the field of histopathology, the domain lacks a comprehensive evaluation of state-of-the-art models based on essential but complementary quality requirements beyond a mere classification…

图像与视频处理 · 电气工程与系统科学 2023-05-11 Maximilian Springenberg , Annika Frommholz , Markus Wenzel , Eva Weicken , Jackie Ma , Nils Strodthoff

Virtual stain transfer is a promising area of research in Computational Pathology, which has a great potential to alleviate important limitations when applying deeplearningbased solutions such as lack of annotations and sensitivity to a…

计算机视觉与模式识别 · 计算机科学 2022-10-19 Jelica Vasiljević , Friedrich Feuerhake , Cédric Wemmert , Thomas Lampert

Histopathological diagnoses of tumors in tissue biopsy after Hematoxylin and Eosin (H&E) staining is the gold standard for oncology care. H&E staining is slow and uses dyes, reagents and precious tissue samples that cannot be reused.…

Automatization of the diagnosis of any kind of disease is of great importance and it's gaining speed as more and more deep learning solutions are applied to different problems. One of such computer aided systems could be a decision support…

计算机视觉与模式识别 · 计算机科学 2018-04-24 Tomas Iesmantas , Robertas Alzbutas

Deep learning has recently gained popularity in digital pathology due to its high prediction quality. However, the medical domain requires explanation and insight for a better understanding beyond standard quantitative performance…

Photon Absorption Remote Sensing (PARS) enables label-free imaging of subcellular morphology by observing biomolecule specific absorption interactions. Coupled with deep-learning, PARS produces label-free virtual Hematoxylin and Eosin (H&E)…

Hypoxia occurs when tumour cells outgrow their blood supply, leading to regions of low oxygen levels within the tumour. Calculating hypoxia levels can be an important step in understanding the biology of tumours, their clinical progression…

计算机视觉与模式识别 · 计算机科学 2023-11-22 Petru Manescu , Joseph Geradts , Delmiro Fernandez-Reyes

Spatial transcriptomics (ST) enables gene expression mapping within anatomical context but remains costly and low-throughput. Hematoxylin and eosin (H\&E) staining offers rich morphology yet lacks molecular resolution. We present…

Medical Vision-language models (VLMs) have shown remarkable performances in various medical imaging domains such as histo\-pathology by leveraging pre-trained, contrastive models that exploit visual and textual information. However,…

The interactions between tumor cells and the tumor microenvironment (TME) dictate therapeutic efficacy of radiation and many systemic therapies in breast cancer. However, to date, there is not a widely available method to reproducibly…

We provide in this paper a comprehensive comparison of various transfer learning strategies and deep learning architectures for computer-aided classification of adult-type diffuse gliomas. We evaluate the generalizability of out-of-domain…

Diagnosis of breast carcinomas has so far been limited to the morphological interpretation of epithelial cells and the assessment of epithelial tissue architecture. Consequently, most of the automated systems have focused on characterizing…

Histopathological analysis is a cornerstone of cancer diagnosis, with Hematoxylin and Eosin (H&E) staining routinely acquired for every patient to visualize cell morphology and tissue architecture. On the other hand, multiplex…

计算机视觉与模式识别 · 计算机科学 2026-03-20 Guillaume Balezo , Roger Trullo , Albert Pla Planas , Etienne Decenciere , Thomas Walter

In digital pathology, many image analysis tasks are challenged by the need for large and time-consuming manual data annotations to cope with various sources of variability in the image domain. Unsupervised domain adaptation based on…

图像与视频处理 · 电气工程与系统科学 2022-05-18 Nassim Bouteldja , Barbara Mara Klinkhammer , Tarek Schlaich , Peter Boor , Dorit Merhof

High-resolution spatial transcriptomics (HR-ST) technologies offer unprecedented insights into tissue architecture but lack standardized frameworks for histological annotation. We present ST2HE, a cross-platform generative framework that…

定量方法 · 定量生物学 2025-10-16 Zhentao Liu , Arun Das , Wen Meng , Yu-Chiao Chiu , Shou-Jiang Gao , Yufei Huang

Double staining in histopathology, particularly for metaplastic breast cancer, typically employs H&E and P63 dyes. However, P63's tissue damage and high cost necessitate alternative methods. This study introduces xAI-CycleGAN, an advanced…

图像与视频处理 · 电气工程与系统科学 2023-12-07 Tibor Sloboda , Lukáš Hudec , Wanda Benešová

Immunohistochemistry (IHC) staining plays a significant role in the evaluation of diseases such as breast cancer. The H&E-to-IHC transformation based on generative models provides a simple and cost-effective method for obtaining IHC images.…

计算机视觉与模式识别 · 计算机科学 2025-02-28 Yifan Jia , Xingda Yu , Zhengyang Ji , Songning Lai , Yutao Yue

The aetiology of head and neck squamous cell carcinoma (HNSCC) involves multiple carcinogens such as alcohol, tobacco and infection with human papillomavirus (HPV). As the HPV infection influences the prognosis, treatment and survival of…

计算机视觉与模式识别 · 计算机科学 2022-06-17 Ruoyu Wang , Syed Ali Khurram , Amina Asif , Lawrence Young , Nasir Rajpoot