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Pancreas

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[Robotic Pancreatic Surgery - Learning Curve and Implementation].

Zentralblatt fur Chirurgie
Minimally invasive resection techniques for the treatment of various pathologies of the pancreas are potentially advantageous for the treated patients in terms of restitution time and postoperative morbidity, but are a technical challenge for the res...

Automated pancreas segmentation and volumetry using deep neural network on computed tomography.

Scientific reports
Pancreas segmentation is necessary for observing lesions, analyzing anatomical structures, and predicting patient prognosis. Therefore, various studies have designed segmentation models based on convolutional neural networks for pancreas segmentation...

Automatic quantitative evaluation of normal pancreas based on deep learning in a Chinese adult population.

Abdominal radiology (New York)
OBJECTIVE: To develop a 3D U-Net-based model for the automatic segmentation of the pancreas using the diameters, volume, and density of normal pancreases among Chinese adults.

Deep learning-based pancreas volume assessment in individuals with type 1 diabetes.

BMC medical imaging
Pancreas volume is reduced in individuals with diabetes and in autoantibody positive individuals at high risk for developing type 1 diabetes (T1D). Studies investigating pancreas volume are underway to assess pancreas volume in large clinical databas...

Multi-scale Selection and Multi-channel Fusion Model for Pancreas Segmentation Using Adversarial Deep Convolutional Nets.

Journal of digital imaging
Organ segmentation from existing imaging is vital to the medical image analysis and disease diagnosis. However, the boundary shapes and area sizes of the target region tend to be diverse and flexible. And the frequent applications of pooling operatio...

Accurate pancreas segmentation using multi-level pyramidal pooling residual U-Net with adversarial mechanism.

BMC medical imaging
BACKGROUND: A novel multi-level pyramidal pooling residual U-Net with adversarial mechanism was proposed for organ segmentation from medical imaging, and was conducted on the challenging NIH Pancreas-CT dataset.

State-of-the-art surgery for pancreatic cancer.

Langenbeck's archives of surgery
BACKGROUND: The d evelopment of surgical techniques and specialization and specifically complication management in pancreatic surgery have improved surgical outcomes as well as oncological results in pancreatic surgery in recent decades. Historical m...

3D spatial priors for semi-supervised organ segmentation with deep convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Fully Convolutional neural Networks (FCNs) are the most popular models for medical image segmentation. However, they do not explicitly integrate spatial organ positions, which can be crucial for proper labeling in challenging contexts.

Robot-assisted pancreatic surgery-optimized operating procedures: set-up, port placement, surgical steps.

Journal of robotic surgery
Even in most complex surgical settings, recent advances in minimal-invasive technologies have made the application of robotic-assisted devices more viable. Due to ever increasing experience and expertise, many large international centers now offer ro...

Dual adversarial convolutional networks with multilevel cues for pancreatic segmentation.

Physics in medicine and biology
Accurate organ segmentation is a relatively challenging subject in medical imaging, especially for the pancreas, whose morphological characteristics are subtle but variable. In this paper, a novel dual adversarial convolutional network with multileve...