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Dataset results
34 results for “IHC”
Inflammatory Responses in the Placenta upon SARS-CoV-2 Infection Late in Pregnancy - IHC data
<p>SARS-CoV-2 infection during pregnancy does not affect the large majority of neonates but presents an increased risk for adverse pregnancy outcome. The effects of SARS-CoV-2 of its recently identified variants on placental function are not well understood. In this study, we investigated the impact of late gestational SARS-CoV-2 infection on the placenta.</p> <p>This dataset of is comprised of 897 images of classic immunohistochemistry for 3 markers in placenta from COVID-19 patients and controls.</p> <p><strong>A full description of the tissues, markers, and donors is available in the metadata.csv file.</strong></p>
Validation data set for automatic blood vessel segmentation in colorectal cancer histology (IHC)
<p><strong>Content</strong></p> <p>This data set contains 100 histological image patches of 1000 * 1000 px size. The samples were immunostained for CD34 (3,3'-Diaminobenzidine, DAB [brown]) with hematoxylin (blue) counterstain.</p> <p>Furthermore, the data set contains a table of blood vessel counts in each image by three blinded observers as well as an automatic count with a method based on the following paper:</p> <p>Kather, Jakob Nikolas et al. "Continuous Representation Of Tumor Microvessel Density And Detection Of Angiogenic Hotspots In Histological Whole-Slide Images". <em>Oncotarget</em> 6.22 (2015): 19163-19176. http://dx.doi.org/10.18632/oncotarget.4383</p> <p><strong>Image format</strong></p> <p>All images are RGB, 0.50 µm per pixel, digitized with an Aperio ScanScope (Aperio/Leica biosystems), magnification 20x. Histological samples are fully anonymized images of formalin-fixed paraffin-embedded human colorectal adenocarcinomas (primary tumors and liver metastases) from our pathology archive (Institute of Pathology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany).</p> <p><strong>Ethics statement</strong></p> <p>All experiments were approved by the institutional ethics board (medical ethics board II, University Medical Center Mannheim, Heidelberg University, Germany; approval 2015-868R-MA). The institutional ethics board waived the need for informed consent for this retrospective analysis of anonymized samples. All experiments were carried out in accordance with the Declaration of Helsinki.</p> <p><strong>Contact</strong></p> <p>For questions, please contact:<br> Dr. Jakob Nikolas Kather<br> http://orcid.org/0000-0002-3730-5348<br> ResearcherID: D-4279-2015</p>
Colorectal adenoma IHC (CDX2) raw files
<p>Colorectal adenoma FFPE tissues, with a thickness of 2.5 µm, were mounted on PEN membrane microscopy slides. Tissues underwent immunohistochemistry staining against the marker CDX2 and were counterstained with hematoxylin. For image acquisition, we utilized the Axio Scan.Z1 from Leica.</p>
Computational IHC-H&E mapping in mouse models of colitis (IHC WSIs from paired H&E-IHC WSIs, Part 1/2)
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Computational IHC-H&E mapping in mouse models of colitis (H&E WSIs from paired H&E-IHC WSIs)
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Deep learning chronic wasting disease (CWD) immunohistochemistry (IHC) image dataset
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Computational IHC-H&E mapping in mouse models of colitis (IHC WSIs from paired H&E-IHC WSIs, Part 2/2)
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Suggestions for changes to the IHC key concepts 2018 - 2022
<p>Suggestions for improvements to the 2018 and 2019 versions of the Informed Health Choices Key Concepts and responses.</p>
Low-Dose Radiation Therapy to the Whole Liver With Gemcitabine and Cisplatin in IHC
ClinicalTrials.gov study NCT02254681. IPD Sharing: Not stated. Countries: 1. Publications: 33.
Trastuzumab Deruxtecan (T-DXd) in Patients Who Have Hormone Receptor-negative and Hormone Receptor-positive HER2-low or HER2 IHC 0 Metastatic Breast Cancer
ClinicalTrials.gov study NCT05950945. IPD Sharing: YES. Countries: 10. Publications: 1.
MIHIC: A multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification
<p>A cohort of 47 TMA sections from 114 patients was collected from Liaoning cancer hospital \& Institute, where each TMA section has the size of 188,416$\times$110,080 pixels (i.e., 42660.87um$\times$24924.15um) at 40$\times$ magnification. TMA sections contain different number of tissue cores, ranging from 28 to 48. After excluding poor quality TMA sections with tissue folding, missing or contamination, there are totally 114 patients. Each patient has tissue cores with 12 different IHC stains, including CD3, CD20, CD34, CD38, CD68, CDK4, cyclin-D1, D2-40, FAP, Ki67, P53, and SMA. Two pathologists have manually labeled clear tissue regions (i.e., without controversy) in TMA sections based on visual examination via Qupath software, where six tissue types including Alveoli, Immune cells, Nerosis, Other, Stroma, Tumor were annotated. Besides the annotated six tissue types, we added one more Background type.</p> <p>To build histological classification models, we split 309,698 image patches in MIHIC dataset into three sets: training, validation and test. Note that image patches extracted from the same annotated tissue region are distributed into the same set, which avoids data leakage during classification model optimization. According to the number of extracted ROIs, train, val and test accounted for 64\%, 16\% and 20\%.</p> <h1>if you use this dataset, please cite:</h1> <pre>@article{wang2024mihic, title={MIHIC: a multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification}, author={Wang, Ranran and Qiu, Yusong and Wang, Tong and Wang, Mingkang and Jin, Shan and Cong, Fengyu and Zhang, Yong and Xu, Hongming}, journal={Frontiers in Immunology}, volume={15}, year={2024}, publisher={Frontiers Media SA} }</pre>
IHC data and analysis of CASR in Kilfeather et al., 2023
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IHC data of TYROBP from Kilfeather et al., 2023
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Image dataset from multiplex IHC stained TMA sections
<p><strong>IHC Cohort:</strong> Multiplex IHC stained histological slides were collected from Liaoning Cancer Hospital and Institute in China. The raw data collected are TMA sections, all of which are obtained from NSCLC patients. Non-overlapping image patches (256*256 pixels) are extracted from TMA sections and manually annotated by our collaborated pathologists via the Qupath software. Initially, seven TMA sections with multiplex stains including CD3, CD20, CD38, CDK4, Cyclin-D1, Ki67, and P53 were used. Except for CD3 stained TMA sections, we randomly cropped 25 image patches from each of these TMA sections, of which 17, 3 and 5 patches are correspondingly used for training, validation, and testing. Note that 18, 3 and 5 CD3 image patches are cropped for building dataset. To suppress over-fitting and enhance generalization of the SRSA-Net, we additionally included 81 annotated image patches from other five TMA sections with stains of CD34, CD68, D2-40, FAP, and SMA into training and validation set. In total, the IHC cohort includes 9,725 manually identified cell nuclei. The numbers of training, validation and testing image patches are 195, 36, and 35, respectively.</p> <p>For the masks, the first channel and the second channel denotes the negative and positive nuclei pixels, respectively. Note that each pixel is labelled from 0 to n, where n is the number of individual nuclei detected. 0 pixels indicate background. Pixel values i indicate that the pixel belongs to the ith nucleus. The last channel marks the information of all the nuclei pixels, where nuclei pixel are left as 0, otherwise 1.</p> <p><strong>fold1: training set</strong></p> <p><strong>fold2: validation set</strong></p> <p><strong>fold3: testing set</strong></p> <p> </p> <h2>if you use this dataset, please cite:</h2> <pre>@article{wang2024simultaneously, title={Simultaneously segmenting and classifying cell nuclei by using multi-task learning in multiplex immunohistochemical tissue microarray sections}, author={Wang, Ranran and Qiu, Yusong and Hao, Xinyu and Jin, Shan and Gao, Junxiu and Qi, Heng and Xu, Qi and Zhang, Yong and Xu, Hongming}, journal={Biomedical Signal Processing and Control}, volume={93}, pages={106143}, year={2024}, publisher={Elsevier} }</pre>
iCAGES-guided Precision Therapy for Cancers in Contrast to Standard Care or IHC-guided Theray
ClinicalTrials.gov study NCT03192501. IPD Sharing: NO. Countries: 1. Publications: 1.
Inactive HBsAg Carriers (IHCs) Treated With Pegylated Interferon α2b Based Intervention Therapy
ClinicalTrials.gov study NCT05451420. IPD Sharing: YES. Countries: 1. Publications: 1.
Second-line Treatment With Icotinib in Esophageal Carcinoma Patients With EGFR Overexpression (IHC 3+) or Positive FISH
ClinicalTrials.gov study NCT01855854. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A set of immunohistochemistry (IHC) images from the human protein atlas (HPA)
<p>A set of immunohistochemistry (IHC) images from the human protein atlas (HPA)</p>
FISH and IHC Images from: Molecular Characterization of the Sea Lamprey Retina Illuminates the Evolutionary Origin of Retinal Cell Types
<p>Fluorescence<em> in situ</em> hybridization and immunohistological images produced in this study.</p>
A Study of Trastuzumab Emtansine in Participants With Human Epidermal Growth Factor Receptor (HER)2 Immunohistochemistry (IHC)-Positive, Locally Advanced or Metastatic Non-Small Cell Lung Cancer (NSCL
ClinicalTrials.gov study NCT02289833. IPD Sharing: Not stated. Countries: 7. Publications: 0.
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International Brain Laboratory public data
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OpenNeuro
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