Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
A Novel Fuzzy DBNet for Medical Image Segmentation
by
Huang, Pei-Chen
, Chang, Sheng-Wen
, Chin, Chiun-Li
, Sun, Tzu-Yu
, Li, Chieh-Yu
, Chen, Ting
, Sharma, Alok Kumar
, Lin, Jun-Cheng
, Lai, Yan-Ming
in
Accuracy
/ Algorithms
/ anteroposterior
/ butterfly network
/ Classification
/ Data mining
/ Datasets
/ Deep learning
/ Diagnostic imaging
/ Fuzzy DBNet
/ Identification
/ Image classification
/ Image segmentation
/ lung X-ray
/ Lungs
/ Machine learning
/ Medical errors
/ Medical imaging
/ Methods
/ pill
/ Pneumothorax
/ posteroanterior
/ Prevention
/ Unmanned aerial vehicles
/ X-rays
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
A Novel Fuzzy DBNet for Medical Image Segmentation
by
Huang, Pei-Chen
, Chang, Sheng-Wen
, Chin, Chiun-Li
, Sun, Tzu-Yu
, Li, Chieh-Yu
, Chen, Ting
, Sharma, Alok Kumar
, Lin, Jun-Cheng
, Lai, Yan-Ming
in
Accuracy
/ Algorithms
/ anteroposterior
/ butterfly network
/ Classification
/ Data mining
/ Datasets
/ Deep learning
/ Diagnostic imaging
/ Fuzzy DBNet
/ Identification
/ Image classification
/ Image segmentation
/ lung X-ray
/ Lungs
/ Machine learning
/ Medical errors
/ Medical imaging
/ Methods
/ pill
/ Pneumothorax
/ posteroanterior
/ Prevention
/ Unmanned aerial vehicles
/ X-rays
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
A Novel Fuzzy DBNet for Medical Image Segmentation
by
Huang, Pei-Chen
, Chang, Sheng-Wen
, Chin, Chiun-Li
, Sun, Tzu-Yu
, Li, Chieh-Yu
, Chen, Ting
, Sharma, Alok Kumar
, Lin, Jun-Cheng
, Lai, Yan-Ming
in
Accuracy
/ Algorithms
/ anteroposterior
/ butterfly network
/ Classification
/ Data mining
/ Datasets
/ Deep learning
/ Diagnostic imaging
/ Fuzzy DBNet
/ Identification
/ Image classification
/ Image segmentation
/ lung X-ray
/ Lungs
/ Machine learning
/ Medical errors
/ Medical imaging
/ Methods
/ pill
/ Pneumothorax
/ posteroanterior
/ Prevention
/ Unmanned aerial vehicles
/ X-rays
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
A Novel Fuzzy DBNet for Medical Image Segmentation
2023
Request now
and choose the collection method
Overview
When doctors are fatigued, they often make diagnostic errors. Similarly, pharmacists may also make mistakes in dispensing medication. Therefore, object segmentation plays a vital role in many healthcare-related areas, such as symptom analysis in biomedical imaging and drug classification. However, many traditional deep-learning algorithms use a single view of an image for segmentation or classification. When the image is blurry or incomplete, these algorithms fail to segment the pathological area or the shape of the drugs accurately, which can then affect subsequent treatment plans. Consequently, we propose the Fuzzy DBNet, which combines the dual butterfly network and the fuzzy ASPP in a deep-learning network and processes images from both sides of an object simultaneously. Our experiments used multi-category pill and lung X-ray datasets for training. The average Dice coefficient of our proposed model reached 95.05% in multi-pill segmentation and 97.05% in lung segmentation. The results showed that our proposed model outperformed other state-of-the-art networks in both applications, demonstrating that our model can use multiple views of an image to obtain image segmentation or identification.
This website uses cookies to ensure you get the best experience on our website.