Akash Awasthi
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View article: ConStruct: Structural Distillation of Foundation Models for Prototype-Based Weakly Supervised Histopathology Segmentation
ConStruct: Structural Distillation of Foundation Models for Prototype-Based Weakly Supervised Histopathology Segmentation Open
Weakly supervised semantic segmentation (WSSS) in histopathology relies heavily on classification backbones, yet these models often localize only the most discriminative regions and struggle to capture the full spatial extent of tissue str…
View article: DualProtoSeg: Simple and Efficient Design with Text- and Image-Guided Prototype Learning for Weakly Supervised Histopathology Image Segmentation
DualProtoSeg: Simple and Efficient Design with Text- and Image-Guided Prototype Learning for Weakly Supervised Histopathology Image Segmentation Open
Weakly supervised semantic segmentation (WSSS) in histopathology seeks to reduce annotation cost by learning from image-level labels, yet it remains limited by inter-class homogeneity, intra-class heterogeneity, and the region-shrinkage ef…
View article: Contrastive Integrated Gradients: A Feature Attribution-Based Method for Explaining Whole Slide Image Classification
Contrastive Integrated Gradients: A Feature Attribution-Based Method for Explaining Whole Slide Image Classification Open
Interpretability is essential in Whole Slide Image (WSI) analysis for computational pathology, where understanding model predictions helps build trust in AI-assisted diagnostics. While Integrated Gradients (IG) and related attribution meth…
View article: CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling
CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Open
Understanding radiologists' eye movement during Computed Tomography (CT) reading is crucial for developing effective interpretable computer-aided diagnosis systems. However, CT research in this area has been limited by the lack of publicly…
View article: Beyond the First Read: AI-Assisted Perceptual Error Detection in Chest Radiography Accounting for Interobserver Variability
Beyond the First Read: AI-Assisted Perceptual Error Detection in Chest Radiography Accounting for Interobserver Variability Open
Chest radiography is widely used in diagnostic imaging. However, perceptual errors -- especially overlooked but visible abnormalities -- remain common and clinically significant. Current workflows and AI systems provide limited support for…
View article: Modeling radiologists’ cognitive processes using a digital gaze twin to enhance radiology training
Modeling radiologists’ cognitive processes using a digital gaze twin to enhance radiology training Open
Predicting human gaze behavior is critical for advancing interactive systems and improving diagnostic accuracy in medical imaging. We present MedGaze, a novel system inspired by the “Digital Gaze Twin” concept, which models radiologists’ c…
View article: Utility, Accuracy, and Bias of Large Language Models as Real-Time Diagnostic Support in Primary Care
Utility, Accuracy, and Bias of Large Language Models as Real-Time Diagnostic Support in Primary Care Open
View article: Structural Chain of Thoughts for Radiology Education
Structural Chain of Thoughts for Radiology Education Open
View article: Structural Chain of Thoughts for Radiology Education
Structural Chain of Thoughts for Radiology Education Open
View article: Beyond the First Read: Ai-Assisted Perceptual Error Detection in Chestradiography Accounting for Interobserver Variability
Beyond the First Read: Ai-Assisted Perceptual Error Detection in Chestradiography Accounting for Interobserver Variability Open
View article: Bridging human and machine intelligence: Reverse-engineering radiologist intentions for clinical trust and adoption
Bridging human and machine intelligence: Reverse-engineering radiologist intentions for clinical trust and adoption Open
View article: GazeSearch: Radiology Findings Search Benchmark
GazeSearch: Radiology Findings Search Benchmark Open
Medical eye-tracking data is an important information source for understanding how radiologists visually interpret medical images. This information not only improves the accuracy of deep learning models for X-ray analysis but also their in…
View article: Deep learning-derived optimal aviation strategies to control pandemics
Deep learning-derived optimal aviation strategies to control pandemics Open
View article: Multimodal Learning and Cognitive Processes in Radiology: MedGaze for Chest X-ray Scanpath Prediction
Multimodal Learning and Cognitive Processes in Radiology: MedGaze for Chest X-ray Scanpath Prediction Open
Predicting human gaze behavior within computer vision is integral for developing interactive systems that can anticipate user attention, address fundamental questions in cognitive science, and hold implications for fields like human-comput…
View article: Enhancing Radiological Diagnosis: A Collaborative Approach Integrating AI and Human Expertise for Visual Miss Correction
Enhancing Radiological Diagnosis: A Collaborative Approach Integrating AI and Human Expertise for Visual Miss Correction Open
Human-AI collaboration to identify and correct perceptual errors in chest radiographs has not been previously explored. This study aimed to develop a collaborative AI system, CoRaX, which integrates eye gaze data and radiology reports to e…
View article: Deep Learning-derived Optimal Aviation Strategies to Control Pandemics
Deep Learning-derived Optimal Aviation Strategies to Control Pandemics Open
The COVID-19 pandemic affected countries across the globe, demanding drastic public health policies to mitigate the spread of infection, which led to economic crises as a collateral damage. In this work, we investigate the impact of human …
View article: Decoding Radiologists’ Intentions: A Novel System for Accurate Region Identification in Chest X-Ray Image Analysis
Decoding Radiologists’ Intentions: A Novel System for Accurate Region Identification in Chest X-Ray Image Analysis Open
In the realm of chest X-ray (CXR) image analysis, radiologists meticulously examine various regions, documenting their observations in reports. The prevalence of errors in CXR diagnoses, particularly among inexperienced radiologists and ho…
View article: Decoding Radiologists' Intentions: A Novel System for Accurate Region Identification in Chest X-ray Image Analysis
Decoding Radiologists' Intentions: A Novel System for Accurate Region Identification in Chest X-ray Image Analysis Open
In the realm of chest X-ray (CXR) image analysis, radiologists meticulously examine various regions, documenting their observations in reports. The prevalence of errors in CXR diagnoses, particularly among inexperienced radiologists and ho…
View article: Video diffusion for early cellular apoptosis forecasting
Video diffusion for early cellular apoptosis forecasting Open
Reliable and early prediction of cell death (apoptosis) is critically important in various areas of biology, particularly in characterizing the effectiveness of cell-based infusion products utilized for cancer immunotherapy. While deep Con…
View article: Apoptosis classification using attention based spatio temporal graph convolution neural network
Apoptosis classification using attention based spatio temporal graph convolution neural network Open
Accurate classification of apoptosis plays an important role in cell biology research. There are many state-of-the-art approaches which use deep CNNs to perform the apoptosis classification but these approaches do not account for the cell …
View article: Anomaly Detection in Satellite Videos using Diffusion Models
Anomaly Detection in Satellite Videos using Diffusion Models Open
The definition of anomaly detection is the identification of an unexpected event. Real-time detection of extreme events such as wildfires, cyclones, or floods using satellite data has become crucial for disaster management. Although severa…
View article: Deep Learning-Derived Optimal Aviation Strategies to Control Pandemics
Deep Learning-Derived Optimal Aviation Strategies to Control Pandemics Open
The COVID-19 pandemic has affected countries across the world, demanding drastic public health policies to mitigate the spread of infection, leading to economic crisis as a collateral damage. In this work, we investigated the impact of hum…
View article: Regional analysis of climate projections using Bias Corrected spatial disaggregated super-resolution convolutional neural networks
Regional analysis of climate projections using Bias Corrected spatial disaggregated super-resolution convolutional neural networks Open
Climate change is very crucial for ecological systems and society. But Global climate models run at coarse spatial resolution which is difficult to do regional analysis. Regional-scale projections can be obtained by a technique called stat…
View article: Deep Learning-based mobile robot for warehouse keeping
Deep Learning-based mobile robot for warehouse keeping Open
As the warehouse plays a crucial role in the supply chain between the manufacturers and end-user or consumers, it is more important to adopt automation in large warehouses and industries. The large e-commerce companies like FLIPKART, AMAZO…