Deep learning in medical imaging and radiation therapy
The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
Accurate screening of COVID-19 using attention-based deep 3D multiple instance learning
Automated Screening of COVID-19 from chest CT is of emergency and importance during
the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 …
the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 …
A survey of feature extraction and fusion of deep learning for detection of abnormalities in video endoscopy of gastrointestinal-tract
A standard screening procedure involves video endoscopy of the Gastrointestinal tract. It is a
less invasive method which is practiced for early diagnosis of gastric diseases. Manual …
less invasive method which is practiced for early diagnosis of gastric diseases. Manual …
Detecting and locating gastrointestinal anomalies using deep learning and iterative cluster unification
DK Iakovidis, SV Georgakopoulos… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a novel methodology for automatic detection and localization of
gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed …
gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed …
Semantic-transferable weakly-supervised endoscopic lesions segmentation
Weakly-supervised learning under image-level labels supervision has been widely applied
to semantic segmentation of medical lesions regions. However, 1) most existing models rely …
to semantic segmentation of medical lesions regions. However, 1) most existing models rely …
Look-behind fully convolutional neural network for computer-aided endoscopy
In this paper, we propose a novel Fully Convolutional Neural Network (FCN) architecture
aiming to aid the detection of abnormalities, such as polyps, ulcers and blood, in …
aiming to aid the detection of abnormalities, such as polyps, ulcers and blood, in …
Weakly-supervised convolutional learning for detection of inflammatory gastrointestinal lesions
SV Georgakopoulos, DK Iakovidis… - … on imaging systems …, 2016 - ieeexplore.ieee.org
Graphic image annotations provide the necessary ground truth information for supervised
machine learning in image-based computer-aided medical diagnosis. Performing such …
machine learning in image-based computer-aided medical diagnosis. Performing such …
Ependymoma and pilocytic astrocytoma: Differentiation using radiomics approach based on machine learning
M Li, H Wang, Z Shang, Z Yang, Y Zhang… - Journal of Clinical …, 2020 - Elsevier
Mandatory accurate and specific diagnosis demands have brought about increased
challenges for radiologists in pediatric posterior fossa tumor prediction and prognosis. With …
challenges for radiologists in pediatric posterior fossa tumor prediction and prognosis. With …
[HTML][HTML] PS-DeVCEM: Pathology-sensitive deep learning model for video capsule endoscopy based on weakly labeled data
We propose a novel pathology-sensitive deep learning model (PS-DeVCEM) for frame-level
anomaly detection and multi-label classification of different colon diseases in video capsule …
anomaly detection and multi-label classification of different colon diseases in video capsule …
Iterative label denoising network: Segmenting male pelvic organs in CT from 3D bounding box annotations
Obtaining accurate segmentation of the prostate and nearby organs at risk (eg, bladder and
rectum) in CT images is critical for radiotherapy of prostate cancer. Currently, the leading …
rectum) in CT images is critical for radiotherapy of prostate cancer. Currently, the leading …