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Pancreas

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Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination.

Biomarkers in medicine
AIM: Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important.

Knowledge-Aided Convolutional Neural Network for Small Organ Segmentation.

IEEE journal of biomedical and health informatics
Accurate and automatic organ segmentation is critical for computer-aided analysis towards clinical decision support and treatment planning. State-of-the-art approaches have achieved remarkable segmentation accuracy on large organs, such as the liver ...

CaSTLe - Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments.

PloS one
Single-cell RNA sequencing (scRNA-seq) is an emerging technology for profiling the gene expression of thousands of cells at the single cell resolution. Currently, the labeling of cells in an scRNA-seq dataset is performed by manually characterizing c...

TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutions.

International journal of computer assisted radiology and surgery
PURPOSE: Deep convolutional neural networks (DCNN) are currently ubiquitous in medical imaging. While their versatility and high-quality results for common image analysis tasks including segmentation, localisation and prediction is astonishing, the l...

Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.

BMC systems biology
BACKGROUND: Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abd...

An application of cascaded 3D fully convolutional networks for medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical st...

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

Medical image analysis
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, as a small, soft, and flexible abdominal organ, the pancreas demonstrates very high inter-patient a...

Safety and feasibility of the robotic platform in the management of surgical sequelae of chronic pancreatitis.

Surgical endoscopy
BACKGROUND/AIM: The application of minimally invasive surgery to chronic pancreatitis (CP) procedures is uncommon. Our objective was to report the safety and feasibility of the robotic approach in the treatment of surgical sequelae of CP, and provide...

Antioxidant and anti-glycation capacities of some medicinal plants and their potential inhibitory against digestive enzymes related to type 2 diabetes mellitus.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Plants preparations are used by traditional medicine in the treatment of various diseases, such as type-2 diabetes mellitus. Some medicinal plants are capable of controlling the complications of this metabolic disease ...

Improved perioperative outcomes of laparoscopic distal pancreatosplenectomy: modified lasso technique.

ANZ journal of surgery
BACKGROUND: Simultaneous division of the splenic artery, splenic vein and pancreatic parenchyma during laparoscopic distal pancreatosplenectomy (LDPS) is known as the lasso technique, which is considered to be simple to perform. However, the original...