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A Quick Look Under the Skin

A Quick Look Under the Skin
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Bjoern Menze , Technical University Of Munich , Technical University Of Munich Germany , Technical University , தொழில்நுட்ப பல்கலைக்கழகம் ஆஃப் முனிச் , தொழில்நுட்ப பல்கலைக்கழகம் ஆஃப் முனிச் ஜெர்மனி , தொழில்நுட்ப பல்கலைக்கழகம் ,

Quick look under skin

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Quick look under skin
Imaging techniques enable a detailed look inside an organism. But interpreting the data is time-consuming and requires a great deal of experience. Artificial neural networks open up new possibilities: They require just seconds to interpret whole-body scans of mice and to segment and depict the organs in colors, instead of in various shades of gray. This facilitates the analysis considerably.
How big is the liver? Does it change if medication is taken? Is the kidney inflamed? Is there a tumor in the brain and did metastases already develop? In order to answer such questions, bioscientists and doctors to date had to screen and interpret a wealth of data. ....

Zhouyi Rong , Fernando Navarro , Javier Coronel , Chenchen Pan , Oliver Schoppe , Bjoernh Menze , Zhongwei Li , Hongcheng Mai , Mihail Ivilinov Todorov , Bjoern Menze , Technical University Of Munich , Institute For Tissue Engineering , Mouse Organ Segmentation , Tissue Engineering , Regenerative Medicine , Professor Bjoern Menze , Image Based Biomedical Modeling , Technical University , Ali Ert , பெர்னாண்டோ நேவாரு , ஜேவியர் கொரோனல் , ஆலிவர் ஸ்கோப் , தொழில்நுட்ப பல்கலைக்கழகம் ஆஃப் முனிச் , நிறுவனம் க்கு திசு பொறியியல் , திசு பொறியியல் , மீளுருவாக்கம் மருந்து ,

Quick look under the skin

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IMAGE: First author Oliver Schoppe in the Center for Translational Cancer Research at the Technical University of Munich.
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Credit: Astrid Eckert / TUM
Imaging techniques enable a detailed look inside an organism. But interpreting the data is time-consuming and requires a great deal of experience. Artificial neural networks open up new possibilities: They require just seconds to interpret whole-body scans of mice and to segment and depict the organs in colors, instead of in various shades of gray. This facilitates the analysis considerably.
How big is the liver? Does it change if medication is taken? Is the kidney inflamed? Is there a tumor in the brain and did metastases already develop? In order to answer such questions, bioscientists and doctors to date had to screen and interpret a wealth of data. ....

Zhouyi Rong , Fernando Navarro , Chenchen Pan , Javier Coronel , Oliver Schoppe , Bjoernh Menze , Zhongwei Li , Mihail Ivilinov Todorov , Hongcheng Mai , Deutsche Forschungsgemeinschaft , Bjoern Menze , Institute For Tissue Engineering , German Federal Ministry Of Education , Technical University Of Munich , University Hospital , Translational Cancer Research , European Union , Institute For Advanced Study , Grant Program , Fritz Thyssen Foundation , Software Campus Initiative , Mouse Organ Segmentation , Tissue Engineering , Regenerative Medicine , Professor Bjoern Menze , Image Based Biomedical Modeling ,

Self-learning algorithms analyze medical imaging data

Self-learning algorithms analyze medical imaging data
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Oliver Schoppe , Bjoern Menze , Technical University Of Munich , Nature Communications , Institute For Tissue Engineering , Astrid Eckert , Mouse Organ Segmentation , Tissue Engineering , Regenerative Medicine , Professor Bjoern Menze , Image Based Biomedical Modeling , Technical University , ஆலிவர் ஸ்கோப் , தொழில்நுட்ப பல்கலைக்கழகம் ஆஃப் முனிச் , இயற்கை தகவல்தொடர்புகள் , நிறுவனம் க்கு திசு பொறியியல் , ஆஸ்ட்ரிட் எக்கேற்ட் , திசு பொறியியல் , மீளுருவாக்கம் மருந்து , படம் அடிப்படையிலானது உயிர் மருத்துவ மாடலிங் , தொழில்நுட்ப பல்கலைக்கழகம் ,