Results 41 to 50 of about 11,209 (203)

Emerging texture and color enhancement imaging in early gastric cancer [PDF]

Digestive Endoscopy, 2021
Screening endoscopy improves detection and prognosis of patients with gastric cancer. However, even expert endoscopists can miss early gastric cancer under standard white light imaging. Texture and color enhancement imaging (TXI) is an image‐enhanced endoscopy that enhances brightness, surface irregularities such elevation or depression, and subtle ...
Seiichiro Abe, Mai Ego Makiguchi, Satoru Nonaka, Haruhisa Suzuki, Shigetaka Yoshinaga, Yutaka Saito   +5 more
openaire   +2 more sources

Usefulness of texture- and color-enhancement imaging for identifying the bleeding point in a patient with post–endoscopic sphincterotomy bleeding

VideoGIE, 2023
Yuki Tanisaka, MD, PhD, Masafumi Mizuide, MD, PhD, Akashi Fujita, MD, PhD, Rie Shiomi, MD, Takahiro shin, MD, Dai Hirata, MD, Kei Sugimoto, MD, Shomei Ryozawa, MD, PhD   +7 more
doaj   +3 more sources

Detecting colorectal lesions with image-enhanced endoscopy: an updated review from clinical trials [PDF]

Clinical Endoscopy, 2023
Colonoscopy plays an important role in reducing the incidence and mortality of colorectal cancer by detecting adenomas and other precancerous lesions.
Mizuki Nagai, Sho Suzuki, Yohei Minato, Fumiaki Ishibashi, Kentaro Mochida, Ken Ohata, Tetsuo Morishita   +6 more
doaj   +1 more source

Gastric squamous metaplasia observed by image‐enhanced endoscopy

DEN Open, 2023
A 61‐year‐old Helicobacter pylori‐positive female with gastroesophageal reflux disease has undergone surveillance endoscopy every year for 13 years at Tokyo Medical University Hospital.
Eri Iwata, Mitsushige Sugimoto, Yoshika Akimoto, Mariko Hamada, Ryota Niikura, Naoyoshi Nagata, Takao Itoi, Takashi Kawai   +7 more
doaj   +1 more source

Primary Duodenal Adenocarcinoma Expressing Carbonic Anhydrase IX

Case Reports in Gastroenterology, 2022
Primary duodenal adenocarcinoma is a rare malignancy whose carbonic anhydrase IX (CA9) expression remains poorly understood. A 73-year-old man visited our hospital for a medical checkup.
Kimitoshi Kubo, Noriko Kimura, Ryosuke Watanabe, Masayuki Higashino, Mototsugu Kato   +4 more
doaj   +1 more source

Multispectral Fusion of RGB and NIR Images Using Weighted Least Squares and Convolution Neural Networks

IEEE Open Journal of Signal Processing, 2021
In low light condition, color (RGB) images captured by visible sensors suffer from severe noise causing loss of colors and textures. However, near infrared (NIR) images captured by NIR sensors are robust to noise even in low light condition without color.
Cheolkon Jung, Qihui Han, Kailong Zhou, Yuanquan Xu   +3 more
doaj   +1 more source

Automatic hazy image enhancement via haze distribution estimation

Advances in Mechanical Engineering, 2018
Since the impact of haze on outdoor imaging varies sharply with the scene depth, hazy image enhancement proves to be a challenging task. In this article, we propose an adaptive image enhancement method for haze removal.
Xuemei Wang, Mingye Ju, Dengyin Zhang
doaj   +1 more source

ColorMedGAN: A Semantic Colorization Framework for Medical Images

Applied Sciences, 2023
Colorization for medical images helps make medical visualizations more engaging, provides better visualization in 3D reconstruction, acts as an image enhancement technique for tasks such as segmentation, and makes it easier for non-specialists to ...
Shaobo Chen, Ning Xiao, Xinlai Shi, Yuer Yang, Huaning Tan, Jiajuan Tian, Yujuan Quan   +6 more
doaj   +1 more source

Enhancing Capabilities Of Texture Extraction For Color Image Retrieval

, 2007
Content-Based Image Retrieval has been a major area of research in recent years. Efficient image retrieval with high precision would require an approach which combines usage of both the color and texture features of the image. In this paper we propose a method for enhancing the capabilities of texture based feature extraction and further demonstrate ...
Pranam Janney, G. Sridhar, V. Sridhar
openaire   +2 more sources

Attention‐based multi‐channel feature fusion enhancement network to process low‐light images

IET Image Processing, 2022
In realistic low‐light environments, images captured by imaging devices often have problems such as low brightness and low contrast, serious loss of detail information, and a large amount of noise, posing major challenges to computer vision tasks.
Xintao Xu, Jinjiang Li, Zhen Hua, Linwei Fan   +3 more
doaj   +1 more source