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Sökning: id:"swepub:oai:DiVA.org:kth-308867" > Convolutional neura...

Convolutional neural networks for segmentation of FIB-SEM nanotomography data from porous polymer films for controlled drug release

Skärberg, F. (författare)
RISE,Jordbruk och livsmedel
Fager, Cecilia (författare)
KTH,Fiber- och polymerteknologi,Department of Physics, Chalmers University of Technology, Göteborg, Sweden,Chalmers tekniska högskola,Chalmers University of Technology,Kungliga Tekniska Högskolan (KTH),Royal Institute of Technology (KTH),Chalmers University of Technology, Sweden; KTH Royal Institute of Technology, Sweden
Mendoza-Lara, F. (författare)
AstraZeneca AB
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Josefson, M. (författare)
AstraZeneca AB,AstraZeneca, Sweden
Olsson, Eva, 1960 (författare)
Chalmers tekniska högskola,Chalmers University of Technology,Chalmers University of Technology, Sweden
Lorén, Niklas, 1970 (författare)
RISE,Jordbruk och livsmedel,Chalmers University of Technology, Sweden
Röding, Magnus, 1984 (författare)
RISE,Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,Jordbruk och livsmedel,Chalmers University of Technology, Sweden; University of Gothenburg, Sweden
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 (creator_code:org_t)
2021-05-04
2021
Engelska.
Ingår i: Journal of Microscopy. - : John Wiley and Sons Inc. - 0022-2720 .- 1365-2818. ; 283:1, s. 51-63
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Phase-separated polymer films are commonly used as coatings around pharmaceutical oral dosage forms (tablets or pellets) to facilitate controlled drug release. A typical choice is to use ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. When an EC/HPC film is in contact with water, the leaching out of the water-soluble HPC phase produces an EC film with a porous network through which the drug is transported. The drug release can be tailored by controlling the structure of this porous network. Imaging and characterization of such EC porous films facilitates understanding of how to control and tailor film formation and ultimately drug release. Combined focused ion beam and scanning electron microscope (FIB-SEM) tomography is a well-established technique for high-resolution imaging, and suitable for this application. However, for segmenting image data, in this case to correctly identify the porous network, FIB-SEM is a challenging technique to work with. In this work, we implement convolutional neural networks for segmentation of FIB-SEM image data. The data are acquired from three EC porous films where the HPC phases have been leached out. The three data sets have varying porosities in a range of interest for controlled drug release applications. We demonstrate very good agreement with manual segmentations. In particular, we demonstrate an improvement in comparison to previous work on the same data sets that utilized a random forest classifier trained on Gaussian scale-space features. Finally, we facilitate further development of FIB-SEM segmentation methods by making the data and software used open access. 

Ämnesord

NATURVETENSKAP  -- Kemi -- Polymerkemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences -- Polymer Chemistry (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Kemiteknik -- Polymerteknologi (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Chemical Engineering -- Polymer Technologies (hsv//eng)
NATURVETENSKAP  -- Kemi -- Annan kemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences -- Other Chemistry Topics (hsv//eng)
NATURVETENSKAP  -- Matematik (hsv//swe)
NATURAL SCIENCES  -- Mathematics (hsv//eng)

Nyckelord

controlled drug release
convolutional neural networks
deep learning
focused ion beam scanning electron microscopy
image analysis
machine learning
microstructure
polymer films
porous materials
semantic segmentation
alcohol
ethyl cellulose
hydroxypropylcellulose
porous polymer
polymer
water
Article
artificial neural network
comparative study
controlled study
convolutional neural network
data accuracy
electron beam
feature extraction
focused ion beam
image segmentation
kernel method
molecular weight
prediction
scanning electron microscopy
drug release
porosity
Drug Liberation
Neural Networks
Computer
Polymers
controlled drug release
convolutional neural networks
deep learning
focused ion beam scanning electron microscopy
image analysis
machine learning
microstructure
polymer films
porous materials
semantic segmentation

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