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Showing 1 to 20 of 228 for “"Histopathology"”.

  1. Tumour Localisation in Histopathology Images

    … in a rotation invariant manner, suitable for histopathology images. To incorporate essential contextual information, methods which utilise posterior tumour probabilities in an iterative manner are proposed. Results showed pixel-level agreements between automated and manual tumour segmentation …

    dundee Repository record for Tumour Localisation in Histopathology Images (opens in a new tab)

  2. Deep learning for processing histopathology images

    Histopathology is the study and diagnosis of disease via tissue microscopy and it is currently the ‘gold-standard‘ in formally diagnosing many types of disease including cancers.<br/>Due to increasing workloads on pathologists, there is a growing need for automated image analysis pipelines that are …

    qu-belfast Repository record for Deep learning for processing histopathology images (opens in a new tab)

  3. Multiphoton microscopy for stain-free slide-free histopathology

    … for human breast cancer and facilitate automated histopathology. We introduce single-shot label-free autofluorescence-multiharmonic (SLAM) microscopy, a single-excitation source nonlinear imaging platform that uses a custom-designed excitation window at 1110 nm and shaped ultrafast pulses at 10 …

    uiuc Repository record for Multiphoton microscopy for stain-free slide-free histopathology (opens in a new tab)

  4. Label-free breast histopathology using quantitative phase imaging

    … In spite of this assessment, the standard histopathology of breast cancer still relies on manual microscopic examination of stained tissue. Being qualitative and manual in nature, this standard diagnostic procedure can suffer from inter-observer variation and low-throughput. In addition, …

    uiuc Repository record for Label-free breast histopathology using quantitative phase imaging (opens in a new tab)

  5. Data Standardization and Machine Learning Models for Histopathology

    Machine learning can provide insight and support for a variety of decisions. In some areas of medicine, decision-support models are capable of assisting healthcare practitioners in making accurate diagnoses. In this work we explored the application of these techniques to distinguish between two …

    vt Repository record for Data Standardization and Machine Learning Models for Histopathology (opens in a new tab)

  6. Near infrared Raman spectroscopy for human artery histochemistry and histopathology

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.

    mit Repository record for Near infrared Raman spectroscopy for human artery histochemistry and histopathology (opens in a new tab)

  7. Segregation similarity loss in morphological ranking of image search in histopathology

    Histopathology is the study of changes in tissue caused by diseases such as cancer. It plays an important role to diagnose the cancers. Regarding the large variation of many cancers types, and the large size of Whole Slide Images (WSIs), the analysis of histopathology images is challenging. To come …

    uoit Repository record for Segregation similarity loss in morphological ranking of image search in histopathology (opens in a new tab)

  8. Molecular vibrational diagnostics - from quantum state stability to real time histopathology

    … desired for early disease diagnosis. Stained histopathology is the gold standard, but remains a subjective practice on processed tissue taking from hours to days. We present proof of principle results showcasing the potential of nonlinear interferometric vibrational imaging (NIVI) for cancer …

    uiuc Repository record for Molecular vibrational diagnostics - from quantum state stability to real time histopathology (opens in a new tab)

  9. Translation of infrared spectroscopic imaging for digital histopathology of clinical specimens

    Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-12-01

    uiuc Repository record for Translation of infrared spectroscopic imaging for digital histopathology of clinical specimens (opens in a new tab)

  10. Immune Infiltrates in Breast Cancer: Clinical Significance from Histopathology to Prognosis

    Though breast cancer has been traditionally regarded as non-immunogenic, in recent years, evidence has increasingly shown that patient immune responses play a central role in prognosis. Overall, increased tumour infiltrating lymphocyte (TIL) counts are associated with better outcomes. However, the …

    cambridge Repository record for Immune Infiltrates in Breast Cancer: Clinical Significance from Histopathology to Prognosis (opens in a new tab)

  11. Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images

    … aligned image and text models on gigapixel histopathology whole slide images, enabling multiple downstream diagnostic tasks to be carried out by pretrained encoders without requiring any additional labels. MI-Zero reformulates zero-shot transfer under the framework of multiple instance …

    mit Repository record for Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images (opens in a new tab)

  12. Understanding compound-induced histopathology in rat liver using gene expression network methods

    … data-driven methods led to the novel creation of histopathology signatures, which accounts for dependence between histopathology observations (Chapter 2). Six toxic groups were determined for DrugMatrix and 13 for Open TG-GATEs, and were analysed with a view to enable classification, namely, what …

    cambridge Repository record for Understanding compound-induced histopathology in rat liver using gene expression network methods (opens in a new tab)

  13. Interpretable Tumor Localization in Bladder Cancer Histopathology Using Deep Multiple Instance Learning

    Deep learning has emerged in cancer histopathology as a tool for predicting clinical and molecular properties of a patient’s disease, thereby connecting slide with function. This concept is especially relevant to bladder cancer, where molecular and histopathologic heterogeneity is known to impact …

    mit Repository record for Interpretable Tumor Localization in Bladder Cancer Histopathology Using Deep Multiple Instance Learning (opens in a new tab)

  14. Texture-based Deep Neural Network for Histopathology Cancer Whole Slide Image (WSI) Classification

    <p>Automatic histopathological Whole Slide Image (WSI) analysis for cancer classification has been highlighted along with the advancements in microscopic imaging techniques. However, manual examination and diagnosis with WSIs is time-consuming and tiresome. Recently, deep convolutional neural …

    kennesaw Repository record for Texture-based Deep Neural Network for Histopathology Cancer Whole Slide Image (WSI) Classification (opens in a new tab)

  15. DEEP LEARNING ALGORITHM FOR MOLECULAR CLASSIFICATION OF ENDOMETRIAL CANCER FROM WHOLE SLIDE HISTOPATHOLOGY IMAGES

    Endometrial cancer (EC) is a common malignancy whose molecular classification (POLEmut, MMRd, p53-abn, NSMP) guides prognosis and treatment. While MMRd and p53-abn can be assessed through IHC, POLEmut identification requires gene sequencing, which is costly and often unavailable. In this study, we …

    milano Repository record for DEEP LEARNING ALGORITHM FOR MOLECULAR CLASSIFICATION OF ENDOMETRIAL CANCER FROM WHOLE SLIDE HISTOPATHOLOGY IMAGES (opens in a new tab)

  16. Registration of pre-operative lung cancer PET/CT scans with post-operative histopathology images

    … they are compared against the gold standard of histopathology.The aim of this retrospective study was to build a robust imaging framework for registering in vivo and post-operative scans from lung cancer patients, in order to have a global, pathology-validated multimodality map of the tumour and …

    strathclyde Repository record for Registration of pre-operative lung cancer PET/CT scans with post-operative histopathology images (opens in a new tab)

  17. Some Observations on the Histogenesis and Histopathology of Echinococcus Alveolaris (Klemm), in White Mice

    Made available in DSpace on 2014-12-04T22:45:57Z (GMT). No. of bitstreams: 1 0016411.pdf: 8343032 bytes, checksum: b526d559d13891651322a6193203af77 (MD5) Previous issue date: 1956

    uiuc Repository record for Some Observations on the Histogenesis and Histopathology of Echinococcus Alveolaris (Klemm), in White Mice (opens in a new tab)

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