Search Results for author: Philip Meyer

Found 4 papers, 3 papers with code

Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer

no code implementations • 25 Mar 2024 • Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Daniel Hieber, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Frank Kramer, Iñaki Soto-Rey, Johannes Raffler

Overall, this study lays the groundwork for enhanced Gleason grading systems, potentially improving diagnostic efficiency for prostate cancer.

Image Classification

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DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks

1 code implementation • 25 Mar 2024 • Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Iñaki Soto-Rey, Johannes Raffler

Our tool contributes to the wider adoption of AI-based Gleason grading within the research community and paves the way for broader clinical application of deep learning models in digital pathology.

Image Classification Specificity

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MISm: A Medical Image Segmentation Metric for Evaluation of weak labeled Data

1 code implementation • 24 Oct 2022 • Dennis Hartmann, Verena Schmid, Philip Meyer, Iñaki Soto-Rey, Dominik Müller, Frank Kramer

Performance measures are an important tool for assessing and comparing different medical image segmentation algorithms.

Image Segmentation Medical Image Segmentation +2

100

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MISeval: a Metric Library for Medical Image Segmentation Evaluation

1 code implementation • 23 Jan 2022 • Dominik Müller, Dennis Hartmann, Philip Meyer, Florian Auer, Iñaki Soto-Rey, Frank Kramer

Thus, we propose our open-source publicly available Python package MISeval: a metric library for Medical Image Segmentation Evaluation.

Image Segmentation Medical Image Segmentation +2

100

Paper
Code

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