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Luis Antonio De Souza
Researcher at Regensburg University of Applied Sciences
Publications - 17
Citations - 428
Luis Antonio De Souza is an academic researcher from Regensburg University of Applied Sciences. The author has contributed to research in topics: Feature extraction & Support vector machine. The author has an hindex of 9, co-authored 16 publications receiving 283 citations. Previous affiliations of Luis Antonio De Souza include Federal University of São Carlos & Sao Paulo State University.
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Journal ArticleDOI
Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma
Alanna Ebigbo,Robert Mendel,Andreas Probst,Johannes Manzeneder,Luis Antonio De Souza,Luis Antonio De Souza,João Paulo Papa,João Paulo Papa,Christoph Palm,Helmut Messmann +9 more
TL;DR: Based on still images from two databases, the diagnosis of EAC by CAD-DL reached sensitivities/specificities of 97%/88% (Augsburg data) and 92%/100% (Medical Image Computing and Computer-Assisted Intervention [MICCAI] data) for white light (WL) images and 94%/80% for narrow band images (NBI) (Augburg data), respectively.
Journal ArticleDOI
Real-time use of artificial intelligence in the evaluation of cancer in Barrett’s oesophagus
Alanna Ebigbo,Robert Mendel,Andreas Probst,Johannes Manzeneder,Friederike Prinz,Luis Antonio De Souza,João Paulo Papa,Christoph Palm,Helmut Messmann +8 more
TL;DR: To enable the seamless integration of AI-based image classification into the clinical workflow, a previous system was developed further to increase the speed of image analysis for classification and the resolution of the dense prediction, which shows the color-coded spatial distribution of cancer probabilities.
Journal ArticleDOI
A survey on Barrett's esophagus analysis using machine learning.
Luis Antonio De Souza,Christoph Palm,Robert Mendel,Christian Hook,Alanna Ebigbo,Andreas Probst,Helmut Messmann,Silke Anna Theresa Weber,João Paulo Papa +8 more
TL;DR: This work presents a systematic review concerning recent studies and technologies of machine learning for Barrett's esophagus diagnosis and treatment, and reviewed recent studies focused on the automatic detection of the neoplastic region for classification purposes using machine learning methods.
Journal ArticleDOI
A technical review of artificial intelligence as applied to gastrointestinal endoscopy: clarifying the terminology
Alanna Ebigbo,Christoph Palm,Andreas Probst,Robert Mendel,Johannes Manzeneder,Friederike Prinz,Luis Antonio De Souza,Luis Antonio De Souza,João Paulo Papa,Peter D. Siersema,Helmut Messmann +10 more
TL;DR: A physician-engineer co-authored review explains the basic technical aspects of AI and provides a comprehensive overview of recent publications on AI in gastrointestinal endoscopy.
Journal ArticleDOI
Endoscopic prediction of submucosal invasion in Barrett's cancer with the use of artificial intelligence: a pilot study.
Alanna Ebigbo,Robert Mendel,Tobias Rückert,Laurin Schuster,Andreas Probst,Johannes Manzeneder,Friederike Prinz,Matthias Mende,Ingo Steinbrück,Siegbert Faiss,David Rauber,David Rauber,Luis Antonio De Souza,Luis Antonio De Souza,João Paulo Papa,Pierre Henri Deprez,Tsuneo Oyama,Akiko Takahashi,Stefan Seewald,Prateek Sharma,Michael F. Byrne,Christoph Palm,Christoph Palm,Helmut Messmann +23 more
TL;DR: This pilot study demonstrates the first multicenter application of an AI-based system in the prediction of submucosal invasion in endoscopic images of Barrett's cancer and scores equal to international experts in the field.