scholarly journals DeepMapi: a Fully Automatic Registration Method for Mesoscopic Optical Brain Images Using Convolutional Neural Networks

2020 ◽  
Author(s):  
Hong Ni ◽  
Zhao Feng ◽  
Yue Guan ◽  
Xueyan Jia ◽  
Wu Chen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Automatic Registration ◽  
Brain Images ◽  
Registration Method ◽  
Fully Automatic

scholarly journals Semantic Segmentation of Cerebellum in 2D Fetal Ultrasound Brain Images using Convolutional Neural Networks

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Vishal Singh ◽  
Pradeeba Sridar ◽  
Jinman Kim ◽  
Ralph Nanan ◽  
N. Poornima ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Semantic Segmentation ◽  
Fetal Ultrasound ◽  
Brain Images

Fully automatic segmentation of sinonasal cavity and pharyngeal airway based on convolutional neural networks

2021 ◽  
Vol 159 (6) ◽  
pp. 824-835.e1
Author(s):  
Rosalia Leonardi ◽  
Antonino Lo Giudice ◽  
Marco Farronato ◽  
Vincenzo Ronsivalle ◽  
Silvia Allegrini ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Automatic Segmentation ◽  
Pharyngeal Airway ◽  
Fully Automatic

scholarly journals Fully Automatic Cell Segmentation with Fourier Descriptors

2021 ◽  
Author(s):  
Dominik Hirling ◽  
Peter Horvath
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Fundamental Problem ◽  
Cell Segmentation ◽  
Fourier Descriptors ◽  
Control Points ◽  
Coefficient Vector ◽  
Fully Automatic ◽  
High Level ◽  
And Control

Cell segmentation is a fundamental problem in biology for which convolutional neural networks yield the best results nowadays. In this paper, we present HarmonicNet, a network, which is a modification of the popular StarDist and SplineDist architectures. While StarDist and SplineDist describe an object by the lengths of equiangular rays and control points respectively, our network utilizes Fourier descriptors, predicting a coefficient vector for every pixel on the image, which implicitly define the resulting segmentation. We evaluate our model on three different datasets, and show that Fourier descriptors can achieve a high level of accuracy with a small number of coefficients. HarmonicNet is also capable of accurately segmenting objects that are not star-shaped, a case where StarDist performs suboptimally according to our experiments.

Fully Automatic Segmentation Of The Mandible Based On Convolutional Neural Networks (CNNs)

2021 ◽  
Author(s):  
Antonino Lo Giudice ◽  
Vincenzo Ronsivalle ◽  
Concetto Spampinato ◽  
Rosalia Leonardi
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Automatic Segmentation ◽  
Fully Automatic
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