no code implementations • 25 Jan 2024 • Balamurali Murugesan, Sukesh Adiga Vasudeva, Bingyuan Liu, Hervé Lombaert, Ismail Ben Ayed, Jose Dolz
Ensuring reliable confidence scores from deep neural networks is of paramount significance in critical decision-making systems, particularly in real-world domains such as healthcare.
2 code implementations • 30 Jun 2023 • Balamurali Murugesan, Rukhshanda Hussain, Rajarshi Bhattacharya, Ismail Ben Ayed, Jose Dolz
First, modifying only the class token of the text prompt results in a greater impact on the Class Activation Map (CAM), compared to arguably more complex strategies that optimize the context.
Few-Shot Learning Weakly supervised Semantic Segmentation +1
1 code implementation • 11 Mar 2023 • Balamurali Murugesan, Sukesh Adiga V, Bingyuan Liu, Hervé Lombaert, Ismail Ben Ayed, Jose Dolz
Ensuring reliable confidence scores from deep networks is of pivotal importance in critical decision-making systems, notably in the medical domain.
1 code implementation • 9 Sep 2022 • Balamurali Murugesan, Bingyuan Liu, Adrian Galdran, Ismail Ben Ayed, Jose Dolz
Following our observations, we propose a simple and flexible generalization based on inequality constraints, which imposes a controllable margin on logit distances.
no code implementations • 25 Jul 2022 • Nicky Nirlipta Sahoo, Balamurali Murugesan, Ayantika Das, Srinivasa Karthik, Keerthi Ram, Steffen Leonhardt, Jayaraj Joseph, Mohanasankar Sivaprakasam
Preterm babies in the Neonatal Intensive Care Unit (NICU) have to undergo continuous monitoring of their cardiac health.
no code implementations • 5 Jul 2022 • Balamurali Murugesan, Sriprabha Ramanarayanan, Sricharan Vijayarangan, Keerthi Ram, Naranamangalam R Jagannathan, Mohanasankar Sivaprakasam
In our work, we develop deep networks to further improve the quantitative and the perceptual quality of reconstruction.
1 code implementation • MIDL 2019 • Sriprabha Ramanarayanan, Balamurali Murugesan, Keerthi Ram, Mohanasankar Sivaprakasam
We propose a multiple acquisition context based network, called MAC-ReconNet for MRI reconstruction, flexible to multiple acquisition contexts and generalizable to unseen contexts for applicability in real scenarios.
no code implementations • 3 Sep 2021 • Supriti Mulay, Keerthi Ram, Balamurali Murugesan, Mohanasankar Sivaprakasam
A deep learning-based edge adaptive instance normalization style transfer technique for segmenting the coronary arteries, is presented in this paper.
1 code implementation • 17 Apr 2020 • Sricharan Vijayarangan, Vignesh R, Balamurali Murugesan, Preejith SP, Jayaraj Joseph, Mohansankar Sivaprakasam
Furthermore, the model was also evaluated on three other databases.
no code implementations • 11 Apr 2020 • Sricharan Vijayarangan, Balamurali Murugesan, Vignesh R, Preejith SP, Jayaraj Joseph, Mohansankar Sivaprakasam
However, these traditional methods require expert knowledge and are unable to model a wide range of arrhythmia.
1 code implementation • MIDL 2019 • Balamurali Murugesan, Sricharan Vijayarangan, Kaushik Sarveswaran, Keerthi Ram, Mohanasankar Sivaprakasam
In our work, we propose a knowledge distillation (KD) framework for the image to image problems in the MRI workflow in order to develop compact, low-parameter models without a significant drop in performance.
1 code implementation • 8 Jan 2020 • Sriprabha Ramanarayanan, Balamurali Murugesan, Keerthi Ram, Mohanasankar Sivaprakasam
Among them, U-Net has shown to be the baseline architecture for MR image reconstruction.
1 code implementation • 8 Jan 2020 • Balamurali Murugesan, Kaushik Sarveswaran, Vijaya Raghavan S, Sharath M. Shankaranarayana, Keerthi Ram, Mohanasankar Sivaprakasam
Foreground-background class imbalance is a common occurrence in medical images, and U-Net has difficulty in handling class imbalance because of its cross entropy (CE) objective function.
no code implementations • 8 Oct 2019 • José Ignacio Orlando, Huazhu Fu, João Barbossa Breda, Karel van Keer, Deepti. R. Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, Joonho Lee, Joonseok Lee, Xiaoxiao Li, Peng Liu, Shuai Lu, Balamurali Murugesan, Valery Naranjo, Sai Samarth R. Phaye, Sharath M. Shankaranarayana, Apoorva Sikka, Jaemin Son, Anton Van Den Hengel, Shujun Wang, Junyan Wu, Zifeng Wu, Guanghui Xu, Yongli Xu, Pengshuai Yin, Fei Li, Yanwu Xu, Xiulan Zhang, Hrvoje Bogunović
As part of REFUGE, we have publicly released a data set of 1200 fundus images with ground truth segmentations and clinical glaucoma labels, currently the largest existing one.
1 code implementation • 25 Aug 2019 • Balamurali Murugesan, Vijaya Raghavan S, Kaushik Sarveswaran, Keerthi Ram, Mohanasankar Sivaprakasam
Our experiments show that the concept of a context discriminator can be extended to existing GAN based reconstruction models to offer better performance.
1 code implementation • 14 Aug 2019 • Balamurali Murugesan, Kaushik Sarveswaran, Sharath M. Shankaranarayana, Keerthi Ram, Jayaraj Joseph, Mohanasankar Sivaprakasam
For the task of medical image segmentation, fully convolutional network (FCN) based architectures have been extensively used with various modifications.
no code implementations • 29 Mar 2019 • Vignesh Ravichandran, Balamurali Murugesan, Sharath M. Shankaranarayana, Keerthi Ram, Preejith S. P, Jayaraj Joseph, Mohanasankar Sivaprakasam
We further evaluate the signal denoising using Mean Square Error(MSE) and Cross Correlation between model predictions and ground truth.
Ranked #1 on ECG Denoising on UnoViS_auto2012
no code implementations • 12 Feb 2019 • Vignesh Ravichandran, Balamurali Murugesan, Vaishali Balakarthikeyan, Sharath M. Shankaranarayana, Keerthi Ram, Preejith S. P, Jayaraj Joseph, Mohanasankar Sivaprakasam
Recently, due to the widespread adoption of wearable smartwatches with in-built Photoplethysmogram (PPG) sensor, it is being considered as a viable candidate for continuous and unobtrusive respiration monitoring.
1 code implementation • 11 Feb 2019 • Balamurali Murugesan, Kaushik Sarveswaran, Sharath M. Shankaranarayana, Keerthi Ram, Mohanasankar Sivaprakasam
We also propose a new joint loss function for the proposed architecture.
no code implementations • 25 Jan 2019 • Balamurali Murugesan, Kaushik Sarveswaran, Sharath M. Shankaranarayana, Keerthi Ram, Mohanasankar Sivaprakasam
We modify the decoder part of the FCN to exploit class information and the structural information as well.