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Spleen

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Elucidating the interaction dynamics between microswimmer body and immune system for medical microrobots.

Science robotics
The structural design parameters of a medical microrobot, such as the morphology and surface chemistry, should aim to minimize any physical interactions with the cells of the immune system. However, the same surface-borne design parameters are also c...

Deep Learning Algorithm for Automated Segmentation and Volume Measurement of the Liver and Spleen Using Portal Venous Phase Computed Tomography Images.

Korean journal of radiology
OBJECTIVE: Measurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT) volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement, it has limited application...

Multi-to-binary network (MTBNet) for automated multi-organ segmentation on multi-sequence abdominal MRI images.

Physics in medicine and biology
Fully convolutional neural network (FCN) has achieved great success in semantic segmentation. However, the performance of the FCN is generally compromised for multi-object segmentation. Multi-organ segmentation is very common while challenging in the...

Decision-making in pediatric blunt solid organ injury: A deep learning approach to predict massive transfusion, need for operative management, and mortality risk.

Journal of pediatric surgery
BACKGROUND: The principal triggers for intervention in the setting of pediatric blunt solid organ injury (BSOI) are declining hemoglobin values and hemodynamic instability. The clinical management of BSOI is, however, complex. We therefore hypothesiz...

An index based on deep learning-measured spleen volume on CT for the assessment of high-risk varix in B-viral compensated cirrhosis.

European radiology
OBJECTIVES: Deep learning enables an automated liver and spleen volume measurements on CT. The purpose of this study was to develop an index combining liver and spleen volumes and clinical factors for detecting high-risk varices in B-viral compensate...

Identifying gross post-mortem organ images using a pre-trained convolutional neural network.

Journal of forensic sciences
Identifying organs/tissue and pathology on radiological and microscopic images can be performed using convolutional neural networks (CNN). However, there are scant studies on applying CNN to post-mortem gross images of visceral organs. This proof-of-...

Multi-Organ Segmentation Over Partially Labeled Datasets With Multi-Scale Feature Abstraction.

IEEE transactions on medical imaging
Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-organ segmentation. In this paper, we propose a unified training strategy...

Deep learning-enabled multi-organ segmentation in whole-body mouse scans.

Nature communications
Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tedious and error-prone task if done manually. Here, we present a deep learning solution called AIMOS that...

A retrospective comparative study of robotic distal pancreatectomy with or without splenic vessel and spleen preservation.

The surgeon : journal of the Royal Colleges of Surgeons of Edinburgh and Ireland
BACKGROUND: Robotic distal pancreatectomy has been accepted to be safe and effective for pancreatic tail lesion. Whether spleen preservation by preserving the splenic vessels with robot assistance is feasible and beneficial remains controversial. Her...