AIMC Topic: Neuroendocrine Tumors

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Efficient and robust cell detection: A structured regression approach.

Medical image analysis
Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical image analysis methods and computer-aided diagnosis (CAD). It remains a challenging task due to touching cells, inhomogeneous background noise, and l...

Impact of chromogranin A, differentiation, and mitoses in nonfunctional pancreatic neuroendocrine tumors ≤ 2 cm.

The Journal of surgical research
BACKGROUND: Small pancreatic neuroendocrine tumors (PNETs) are a unique subset of pancreatic neoplasms. Chromogranin A (CgA) levels, mitotic rate, and histologic differentiation are often used to characterize PNET behavior. This study evaluates the i...

Deep Voting: A Robust Approach Toward Nucleus Localization in Microscopy Images.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Robust and accurate nuclei localization in microscopy image can provide crucial clues for accurate computer-aid diagnosis. In this paper, we propose a convolutional neural network (CNN) based hough voting method to localize nucleus centroids with hea...

Fast Cell Segmentation Using Scalable Sparse Manifold Learning and Affine Transform-approximated Active Contour.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Efficient and effective cell segmentation of neuroendocrine tumor (NET) in whole slide scanned images is a difficult task due to a large number of cells. The weak or misleading cell boundaries also present significant challenges. In this paper, we pr...

EndoCompass project: research roadmap for pituitary and neuroendocrine tumor endocrinology.

European journal of endocrinology
BACKGROUND: Endocrine science remains underrepresented in European Union research programs despite the fundamental role of hormone health in human wellbeing. Analysis of the CORDIS database reveals a persistent gap between the societal impact of endo...

Uncertainty quantification for deep learning-based metastatic lesion segmentation on whole body PET/CT.

Physics in medicine and biology
Deep learning models are increasingly being implemented for automated medical image analysis to inform patient care. Most models, however, lack uncertainty information, without which the reliability of model outputs cannot be ensured. Several uncerta...

Selection of neuroendocrine markers in diagnostic workup of neuroendocrine neoplasms: The real-world data and machine learning model algorithms.

Cancer cytopathology
BACKGROUND: Accurate diagnosis of neuroendocrine neoplasms (NENs) is challenging, especially in poorly differentiated neuroendocrine carcinomas (NECs). This study was aimed to search the best or best combination of neuroendocrine markers in the diagn...

Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.

The Journal of clinical endocrinology and metabolism
CONTEXT: Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive.