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Parse Challenge 2022: Pulmonary Arteries Segmentation Using Swin U-net Transformer(Swin UNETR) and U-net
Rohan Padhy;Akansh Maurya;Kunal Dasharath Patil;Kalluri Ramakrishna;Ganapathy Krishnamurthi
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
In this paper, we describe a deep neural network architecture based on Swin UNETR and U-Net for segmenting the pulmonary arteries from CT scans. The final segmentation masks were created using an ensemble of six models, three based on Swin UNETR and three based on 3D U-net with residual units. Using this strategy, our group scored 84.36 % on the multi-level dice. We conducted additional investigat...Show More
GAN-based End-to-End Unsupervised Image Registration for RGB-Infrared Image
2020 3rd International Conference on Intelligent Autonomous Systems (ICoIAS)
Year: 2020 | Conference Paper |
Cited by: Papers (3)
Image registration is a pre-processing step used in various computer vision applications. This paper presents an unsupervised image registration for a given pair of RGB and infrared images, with the RGB image used as the reference for infrared. This method exploits the GAN architecture with a spatial transformer module, to synthesize the transformed image using an unsupervised loss criterion. This...Show More
NTIRE 2019 Challenge on Image Enhancement: Methods and Results
Andrey Ignatov;Radu Timofte;Xiaochao Qu;Xingguang Zhou;Ting Liu;Pengfei Wan;Syed Waqas Zamir;Aditya Arora;Salman Khan;Fahad Shahbaz Khan;Ling Shao;Dongwon Park;Se Young Chun;Pablo Navarrete Michelini;Hanwen Liu;Dan Zhu;Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Muhammad Haris;Kazutoshi Akita;Tomoki Yoshida;Greg Shakhnarovich;Norimichi Ukita;Jie Liu;Cheolkon Jung;Raimondo Schettini;Simone Bianco;Claudio Cusano;Flavio Piccoli;Pengju Liu;Kai Zhang;Jingdong Liu;Jiye Liu;Hongzhi Zhang;Wangmeng Zuo;Nelson Chong Ngee Bow;Lai-Kuan Wong;John See;Jinghui Qin;Lishan Huang;Yukai Shi;Pengxu Wei;Wushao Wen;Liang Lin;Zheng Hui;Xiumei Wang;Xinbo Gao;Kanti Kumari;Vikas Kumar Anand;Mahendra Khened;Ganapathy Krishnamurthi
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2019 | Conference Paper |
Cited by: Papers (29)
This paper reviews the first NTIRE challenge on perceptual image enhancement with the focus on proposed solutions and results. The participating teams were solving a real-world photo enhancement problem, where the goal was to map low-quality photos from the iPhone 3GS device to the same photos captured with Canon 70D DSLR camera. The considered problem embraced a number of computer vision subtasks...Show More
NTIRE 2019 Challenge on Image Enhancement: Methods and Results
Andrey Ignatov;Radu Timofte;Xiaochao Qu;Xingguang Zhou;Ting Liu;Pengfei Wan;Syed Waqas Zamir;Aditya Arora;Salman Khan;Fahad Shahbaz Khan;Ling Shao;Dongwon Park;Se Young Chun;Pablo Navarrete Michelini;Hanwen Liu;Dan Zhu;Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Muhammad Haris;Kazutoshi Akita;Tomoki Yoshida;Greg Shakhnarovich;Norimichi Ukita;Jie Liu;Cheolkon Jung;Raimondo Schettini;Simone Bianco;Claudio Cusano;Flavio Piccoli;Pengju Liu;Kai Zhang;Jingdong Liu;Jiye Liu;Hongzhi Zhang;Wangmeng Zuo;Nelson Chong Ngee Bow;Lai-Kuan Wong;John See;Jinghui Qin;Lishan Huang;Yukai Shi;Pengxu Wei;Wushao Wen;Liang Lin;Zheng Hui;Xiumei Wang;Xinbo Gao;Kanti Kumari;Vikas Kumar Anand;Mahendra Khened;Ganapathy Krishnamurthi
Year: 2019 | Conference Paper |
Deep-Learning based Identification of Frames Containing Foetal Gender Region During Early Second Trimester Ultrasound Scanning
Praveen Paul Lakra;Ashish Kumar;Narayanaswamy Mohanram;Ganapathy Krishnamurthi;Arun Kumar Thittai
2019 IEEE International Ultrasonics Symposium (IUS)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
Sex-selective abortions, based on ultrasound foetal scanning of pregnant women, is a rampant problem in developing countries like India. Although prenatal gender screening has been outlawed, poor enforcement of it has abetted a steady rise in their number. Currently, the B-scans are displayed on the screen in real-time and the operator can make out the gender from the displayed image. Therefore, e...Show More
Recurrent Attention Mechanism Networks for Enhanced Classification of Biomedical Images
Mazhar Shaikh;Varghese Alex Kollerathu;Ganapathy Krishnamurthi
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
Year: 2019 | Conference Paper |
Cited by: Papers (9)
Convolutional neural networks achieve state of the art results for a variety of tasks. However, this improved performance comes at the cost of performing convolutional operations throughout the entire image. Resizing of images to manageable levels is one of the often used techniques so as to reduce this computational overhead. On medical images, lesions are represented by a minuscule proportion of...Show More
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
Olivier Bernard;Alain Lalande;Clement Zotti;Frederick Cervenansky;Xin Yang;Pheng-Ann Heng;Irem Cetin;Karim Lekadir;Oscar Camara;Miguel Angel Gonzalez Ballester;Gerard Sanroma;Sandy Napel;Steffen Petersen;Georgios Tziritas;Elias Grinias;Mahendra Khened;Varghese Alex Kollerathu;Ganapathy Krishnamurthi;Marc-Michel Rohé;Xavier Pennec;Maxime Sermesant;Fabian Isensee;Paul Jäger;Klaus H. Maier-Hein;Peter M. Full;Ivo Wolf;Sandy Engelhardt;Christian F. Baumgartner;Lisa M. Koch;Jelmer M. Wolterink;Ivana Išgum;Yeonggul Jang;Yoonmi Hong;Jay Patravali;Shubham Jain;Olivier Humbert;Pierre-Marc Jodoin
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been the subject of intense research over the past decades. In this paper, we introduce the “Automatic Cardiac Diagnosis Challenge” dataset (ACDC), the large...Show More
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
Olivier Bernard;Alain Lalande;Clement Zotti;Frederick Cervenansky;Xin Yang;Pheng-Ann Heng;Irem Cetin;Karim Lekadir;Oscar Camara;Miguel Angel Gonzalez Ballester;Gerard Sanroma;Sandy Napel;Steffen Petersen;Georgios Tziritas;Elias Grinias;Mahendra Khened;Varghese Alex Kollerathu;Ganapathy Krishnamurthi;Marc-Michel Rohé;Xavier Pennec;Maxime Sermesant;Fabian Isensee;Paul Jäger;Klaus H. Maier-Hein;Peter M. Full;Ivo Wolf;Sandy Engelhardt;Christian F. Baumgartner;Lisa M. Koch;Jelmer M. Wolterink;Ivana Išgum;Yeonggul Jang;Yoonmi Hong;Jay Patravali;Shubham Jain;Olivier Humbert;Pierre-Marc Jodoin
Hypothesis Validation of Far-Wall Brightness in Carotid-Artery Ultrasound for Feature-Based IMT Measurement Using a Combination of Level-Set Segmentation and Registration
Filippo Molinari;Ganapathy Krishnamurthi;U. Rajendra Acharya;S. Vinitha Sree;Guang Zeng;Luca Saba;Andrew Nicolaides;Jasjit S. Suri
Intima-media thickness (IMT) is now being considered as an indicator of atherosclerosis. Our group has developed several feature-based IMT measurement algorithms such as the Completely Automated Layer EXtraction (CALEX) (which is a class of patented AtheroEdge Systems from Global Biomedical Technologies, Inc., CA, USA). These methods are based on the hypothesis that the highest pixel intensities a...Show More
Hypothesis Validation of Far-Wall Brightness in Carotid-Artery Ultrasound for Feature-Based IMT Measurement Using a Combination of Level-Set Segmentation and Registration
Filippo Molinari;Ganapathy Krishnamurthi;U. Rajendra Acharya;S. Vinitha Sree;Guang Zeng;Luca Saba;Andrew Nicolaides;Jasjit S. Suri
Atheromatic™: Symptomatic vs. asymptomatic classification of carotid ultrasound plaque using a combination of HOS, DWT & texture
U Rajendra Acharya;Oliver Faust;S. Vinitha Sree;Ang Peng Chuan Alvin;Ganapathy Krishnamurthi;Jos´e C. R. Seabra;João Sanches;Jasjit S Suri
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2011 | Conference Paper |
Cited by: Papers (19)
Quantitative characterization of carotid atherosclerosis and classification into either symptomatic or asymptomatic is crucial in terms of diagnosis and treatment planning for a range of cardiovascular diseases. This paper presents a computer-aided diagnosis (CAD) system (Atheromatic™, patented technology from Biomedical Technologies, Inc., CA, USA) which analyzes ultrasound images and classifies ...Show More
Functional imaging in small animals using X-ray computed Tomography -study of physiologic measurement reproducibility
G. Krishnamurthi;K.M. Stantz;R. Steinmetz;V.H. Gattone;Minsong Cao;G.D. Hutchins;Yun Liang
X-ray computed tomography (CT) has been traditionally used for morphologic analysis and in the recent past has been used for physiology imaging. This paper seeks to demonstrate functional CT as an effective tool for monitoring changes in tissue physiology associated with disease processes and cellular and molecular level therapeutic processes. We investigated the effect of noise and sampling time ...Show More
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