Publications by authors named "J P M VAN Putten"
Purpose: Molecular tumor boards (MTBs) are considered beneficial for treatment decision making for patients with cancer with uncommon, rare, or complex mutational profiles. The lack of international MTB guidelines results in significant variation in practices and recommendations. Therefore, periodic follow-up is necessary to assess and govern MTB functioning.
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- Pre-training deep learning models for endoscopic image analysis using large datasets like ImageNet is common, but it's unclear if natural image features are the best for medical tasks due to the lack of quality medical imagery.
- This study introduces a new dataset called GastroNet-5M, with over 5 million gastrointestinal endoscopic images, and tests the effectiveness of in-domain pre-training using methods like DINO against pre-training on natural images.
- Results show that self-supervised pre-training with DINO significantly improves model performance on various gastrointestinal tasks, achieving an average boost of 1.63% for ResNet50 and 4.62% for Vision-Transformer-small compared to models trained on natural images.
Background And Aims: Characterization of visible abnormalities in patients with Barrett's esophagus (BE) can be challenging, especially for inexperienced endoscopists. This results in suboptimal diagnostic accuracy and poor interobserver agreement. Computer-aided diagnosis (CADx) systems may assist endoscopists.
View Article and Find Full Text PDFBackground And Aims: This pilot study evaluated the performance of a recently developed computer-aided detection (CADe) system for Barrett's neoplasia during live endoscopic procedures.
Methods: Fifteen patients with a visible lesion and 15 without were included in this study. A CAD-assisted workflow was used that included a slow pullback video recording of the entire Barrett's segment with live CADe assistance, followed by CADe-assisted level-based video recordings every 2 cm of the Barrett's segment.
Glycosylated mucin proteins contribute to the essential barrier function of the intestinal epithelium. The transmembrane mucin MUC13 is an abundant intestinal glycoprotein with important functions for mucosal maintenance that are not yet completely understood. We demonstrate that in human intestinal epithelial monolayers, MUC13 localized to both the apical surface and the tight junction (TJ) region on the lateral membrane.
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