Analysis approaches for histology images; in particular, for appearance normalization.
Histology images of tumor tissue are an important diagnostic and prognostic tool for pathologists. Recently developed molecular methods group tumors into subtypes to further guide treatment decisions, but they are not routinely performed on all …
Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an image-level …
This paper presents a method for automatic color and intensity normalization of digitized histology slides stained with two different agents. In comparison to previous approaches, prior information on the stain vectors is used in the plane estimation …
Through learning small and large-scale image features, we can capture the local and architectural structure of tumor tissue from histology images. This is done by learning a hierarchy of dictionaries using sparse coding, where each level captures …
The purpose of this study is to investigate architectural characteristics of cell arrangements in breast cancer histology images. We propose the use of topological data analysis to summarize the geometric information inherent in tumor cell …
Aims: We apply digital image analysis techniques to study selected types of melanocytic lesions. Methods and Results: We use advanced digital image analysis to compare melanocytic lesions. All comparisons were statistically significant (p < …
This paper presents a method for automatic color and intensity normalization of digitized histology slides stained with two different agents. In comparison to previous approaches, prior information on the stain vectors is used in the estimation …
Inconsistencies in the preparation of histology slides make it difficult to perform quantitative analysis on their results. In this paper we provide two mechanisms for overcoming many of the known inconsistencies in the staining process, thereby …