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Showing 1 to 5 of 5 for “"whole slide image"”.

  1. 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)

  2. Detecting basal cell carcinoma in skin histopathological images using deep learning

    … machine learning techniques that are common in image classification to detect the presence of Basal Cell Carcinoma (BCC) in digital skin histological images. Since digital histology images are extremely large, we first focused on determining the presence of BCC at the patch level, using …

    mit Repository record for Detecting basal cell carcinoma in skin histopathological images using deep learning (opens in a new tab)

  3. Deep learning for digitized histology image analysis

    … to assist pathologists for digitized histology slide analysis. Pre-cervical cancer is generally determined by examining the CIN which is the growth of atypical cells from the basement membrane (bottom) to the top of the epithelium. It has four grades, including: Normal, CIN1, CIN2, and CIN3. In …

    must-thes Repository record for Deep learning for digitized histology image analysis (opens in a new tab)

  4. Exploring the lifecycle of artificial intelligence – deep learning for 1D to 4D biomedical data

    … focus to the segmentation of 2D histological images, which is critical for accurate medical diagnostics, particularly in dermatology. As described in Chapter 4, this work explores advanced semantic segmentation techniques to identify and classify different biological structures within a Whole

    tu-berlin Repository record for Exploring the lifecycle of artificial intelligence – deep learning for 1D to 4D biomedical data (opens in a new tab)

  5. Deep learning on whole-slide images for early detection and risk prediction of oesophageal cancer

    … detected quantity of BE in a pathology slide and the length of the BE segment identified from endoscopy. Beyond oesophageal cancer, the inspection of stained tissue slides by pathologists is essential for the early detection, diagnosis, and monitoring of disease. However, WSIs present a …

    cambridge Repository record for Deep learning on whole-slide images for early detection and risk prediction of oesophageal cancer (opens in a new tab)