Application of deep learning method on ischemic stroke lesion segmentation
Y Zhang, S Liu, C Li, J Wang - Journal of Shanghai Jiaotong University …, 2022 - Springer
Although deep learning methods have been widely applied in medical image lesion
segmentation, it is still challenging to apply it for segmenting ischemic stroke lesions, which …
segmentation, it is still challenging to apply it for segmenting ischemic stroke lesions, which …
Application of convolutional neural network in segmenting brain regions from MRI data
Extracting knowledge from digital images largely depends on how well the mining
algorithms can focus on specific regions of the image. In multimodality image analysis …
algorithms can focus on specific regions of the image. In multimodality image analysis …
Rethinking the dice loss for deep learning lesion segmentation in medical images
Y Zhang, S Liu, C Li, J Wang - Journal of Shanghai Jiaotong University …, 2021 - Springer
Deep learning is widely used for lesion segmentation in medical images due to its
breakthrough performance. Loss functions are critical in a deep learning pipeline, and they …
breakthrough performance. Loss functions are critical in a deep learning pipeline, and they …
3-D RoI-aware U-net for accurate and efficient colorectal tumor segmentation
Segmentation of colorectal cancerous regions from 3-D magnetic resonance (MR) images is
a crucial procedure for radiotherapy. Automatic delineation from 3-D whole volumes is in …
a crucial procedure for radiotherapy. Automatic delineation from 3-D whole volumes is in …
Biomedical sensor image segmentation algorithm based on improved fully convolutional network
J Fan, Q Hua, X Li, Z Wen, M Yang - Measurement, 2022 - Elsevier
Effective use of biomedical sensor image can help locate diseased tissues and tissue
structures clearly presented, and clinical diagnosis and treatment can assist doctors in …
structures clearly presented, and clinical diagnosis and treatment can assist doctors in …
Quantitative analysis of patch-based fully convolutional neural networks for tissue segmentation on brain magnetic resonance imaging
Accurate brain tissue segmentation in magnetic resonance imaging (MRI) has attracted the
attention of medical doctors and researchers since variations in tissue volume and shape …
attention of medical doctors and researchers since variations in tissue volume and shape …
White matter has impaired resting oxygen delivery in sickle cell patients
Although modern medical management has lowered overt stroke occurrence in patients with
sickle cell disease (SCD), progressive white matter (WM) damage remains common. It is …
sickle cell disease (SCD), progressive white matter (WM) damage remains common. It is …
A deep learning algorithm for white matter hyperintensity lesion detection and segmentation
Purpose White matter hyperintensity (WMHI) lesions on MR images are an important
indication of various types of brain diseases that involve inflammation and blood vessel …
indication of various types of brain diseases that involve inflammation and blood vessel …
Blockchain in supply chain management
H Manifavas, I Karamitsos - Heterogeneous Cyber Physical …, 2022 - api.taylorfrancis.com
Tutorials in Circuits and Systems Page 1 CHAPTER 03 Blockchain in Supply Chain
Management Dr. Harry Manifavas Institute of Computer Science Foundation for Research and …
Management Dr. Harry Manifavas Institute of Computer Science Foundation for Research and …
A multi-scale recurrent fully convolution neural network for laryngeal leukoplakia segmentation
B Ji, J Ren, X Zheng, C Tan, R Ji, Y Zhao… - … Signal Processing and …, 2020 - Elsevier
Laryngeal leukoplakia is one kind of precancerous lesions in the larynx. Precise detection
and segmentation of leukoplakia in laryngoscopic images is important for laryngeal disease …
and segmentation of leukoplakia in laryngoscopic images is important for laryngeal disease …