scholarly journals U-Net Plus: Deep Semantic Segmentation for Esophagus and Esophageal Cancer in Computed Tomography Images

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 82867-82877 ◽  
Author(s):  
Shuchao Chen ◽  
Han Yang ◽  
Jiawen Fu ◽  
Weijian Mei ◽  
Shuai Ren ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Esophageal Cancer ◽  
Semantic Segmentation ◽  
Computed Tomography Images

scholarly journals Weakly supervised semantic segmentation of tomographic images in the diagnosis of stroke

2021 ◽  
Vol 2099 (1) ◽  
pp. 012021
Author(s):  
A V Dobshik ◽  
A A Tulupov ◽  
V B Berikov
Keyword(s):  
Computed Tomography ◽  
Network Architecture ◽  
Semantic Segmentation ◽  
Training Data ◽  
Neural Network Architecture ◽  
Brain Images ◽  
Tomographic Images ◽  
Computed Tomography Images ◽  
Segmentation Accuracy ◽  
Weakly Supervised

Abstract This paper presents an automatic algorithm for the segmentation of areas affected by an acute stroke in the non-contrast computed tomography brain images. The proposed algorithm is designed for learning in a weakly supervised scenario when some images are labeled accurately, and some images are labeled inaccurately. Wrong labels appear as a result of inaccuracy made by a radiologist in the process of manual annotation of computed tomography images. We propose methods for solving the segmentation problem in the case of inaccurately labeled training data. We use the U-Net neural network architecture with several modifications. Experiments on real computed tomography scans show that the proposed methods increase the segmentation accuracy.

scholarly journals Diagnosis of COVID-19 Infection Using Three-Dimensional Semantic Segmentation and Classification of Computed Tomography Images

2021 ◽  
Vol 68 (2) ◽  
pp. 2451-2467
Author(s):  
Javaria Amin ◽  
Muhammad Sharif ◽  
Muhammad Almas Anjum ◽  
Yunyoung Nam ◽  
Seifedine Kadry ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
Semantic Segmentation ◽  
Computed Tomography Images

Computed Tomography Brain Images Semantic Segmentation

2017 ◽  
pp. 77-104
Author(s):  
Poonam Fauzdar ◽  
Sarvesh Kumar
Keyword(s):  
Computed Tomography ◽  
Positive Predictive Value ◽  
Euclidean Distance ◽  
Global Analysis ◽  
Semantic Segmentation ◽  
Brain Images ◽  
Minimum Euclidean Distance ◽  
Computed Tomography Images ◽  
Multi Level ◽  
Reduced Time

In this paper we applianced an approach for segmenting brain tumour regions in a computed tomography images by proposing a multi-level fuzzy technique with quantization and minimum computed Euclidean distance applied to morphologically divided skull part. Since the edges identified with closed contours and further improved by adding minimum Euclidean distance, that is why the numerous results that are analyzed are very assuring and algorithm poses following advantages like less cost, global analysis of image, reduced time, more specificity and positive predictive value.

scholarly journals Esophageal Cancer with Bone Marrow Hyperplasia Mimicking Bone Metastasis: Report of a Case

2016 ◽  
Vol 9 (3) ◽  
pp. 679-684 ◽  
Author(s):  
Hiromi Yasuda ◽  
Tadanobu Shimura ◽  
Masato Okigami ◽  
Shigeyuki Yoshiyama ◽  
Masaki Ohi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Bone Marrow ◽  
Esophageal Cancer ◽  
Bone Metastasis ◽  
Bone Lesions ◽  
Histopathological Diagnosis ◽  
Thoracic Esophagus ◽  
Early Stage Disease ◽  
Macroscopic Appearance ◽  
Computed Tomography Images

A 63-year-old man visited the clinic with numbness in the right hand. Magnetic resonance imaging demonstrated multiple low-intensity lesions in the cervical vertebrae and sacrum, which was suspicious of cervical bone metastasis. Fluorodeoxyglucose positron emission tomography/computed tomography revealed areas of increased fluorodeoxyglucose uptake in the thoracic esophagus, sternum and sacrum. A flat, elevated esophageal cancer was identified by upper gastrointestinal endoscopy, and the macroscopic appearance indicated early-stage disease. From the cervical, thoracic and abdominal computed tomography images, there were no metastatic lesions except for the bone lesions. To confirm whether the bone lesions were metastatic, we performed bone biopsy. The histopathological diagnosis was bone marrow hyperplasia. It was crucial for treatment planning to establish whether the lesions were distant metastases. Here, we report a case of esophageal cancer with bone marrow hyperplasia mimicking bone metastasis.

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