Cybermedlife - Therapeutic Actions Ice - Application

Use of external abdominal ice to complete external cephalic version in term breech pregnancy. 📎

Abstract Title: Use of external abdominal ice to complete external cephalic version in term breech pregnancy. Abstract Source: J Am Board Fam Pract. 2005 Jul-Aug;18(4):312-3. PMID: 15994478 Abstract Author(s): Maj Paul F Crawford Article Affiliation: Eglin Air Force Base Family Practice Residency Program, Eglin AFB, Florida 32542, USA. This email address is being protected from spambots. You need JavaScript enabled to view it. Abstract: A 36-year-old multiparous woman with fetus in the breech position applied ice to the fundus of the uterus and achieved successful cephalic version. No other reports of using ice to induce cephalic version are found with MEDLINE search; however, it has been used as a folk remedy. Further research to evaluate the efficacy and safety of ice is needed to determine whether it increases cephalic vaginal birth. Article Published Date : Jul 01, 2005
Therapeutic Actions Ice - Application

NCBI pubmed

The application of convolution neural network based cell segmentation during cryopreservation.

Related Articles The application of convolution neural network based cell segmentation during cryopreservation. Cryobiology. 2018 Sep 13;: Authors: Mbogba MK, Haider Z, Hossain SMC, Huang D, Memon K, Panhwar F, Lei Z, Zhao G Abstract For most of the cells, water permeability and plasma membrane properties play a vital role in the optimal protocol for successful cryopreservation. Measuring the water permeability of cells during subzero temperature is essential. So far, there is no perfect segmentation technique to be used for the image processing task on subzero temperature accurately. The ice formation and variable background during freezing posed a significant challenge for most of the conventional segmentation algorithms. Thus, a robust and accurate segmentation approach that can accurately extract cells from extracellular ice that surrounding the cell boundary is needed. Therefore, we present a novel convolutional neural network (CNN) architecture similar to U-Net but differs from those conventionally used in computer vision to extract all the cell boundaries as they shrank in the engulfing ice. Our images used was obtained from the cryo-stage microscope, and the data was validated using the Hausdorff distance, means ± standard deviation for different methods of segmentation result using our CNN model. The experimental results prove that our CNN model extracts cell borders contour from the background in its subzero state more coherent and effective as compared to other traditional segmentation approaches. PMID: 30219374 [PubMed - as supplied by publisher]