3 citations · 13 across the 11 of their papers we have counts for
12 papers
MUST-PET: MUltimodal Self-supervised learning across Tracers for whole-body PET/CT-based lesion segmentation
Bashirul Azam Biswas, Amartya Bhattacharya, Biratal Raj Wagle +3
Deep learning-based whole-body PET-CT lesion segmentation can support cancer staging, treatment planning, and response assessment, but generalization is limited by scarce annotatio…
Foundation Model-Enabled Efficient Data Sampling (FEEDS): A label-efficient training strategy for pan-cancer, multi-tracer PET/CT datasets
Biratal Raj Wagle, Bashirul Azam Biswas, Grant Chau +5
Automated lesion segmentation in whole-body PET/CT imaging can assist clinicians with cancer detection, staging, and treatment planning across radiotracers and cancer types. Howeve…
Improving PET/CT-Based Whole-Body Lesion Segmentation Using Prediction Uncertainty-Augmented Models
Bashirul Azam Biswas, Biratal Raj Wagle, Zhihan Yang +4
Accurate lesion segmentation from whole-body Positron Emission Tomography (PET)/Computed Tomography (CT) scans is essential for cancer staging and treatment planning. PET provides…
Prostate-Specific Foundation Models for Enhanced Detection of Clinically Significant Cancer
Jeong Hoon Lee, Cynthia Xinran Li, Hassan Jahanandish +14
Accurate prostate cancer diagnosis remains challenging. Even when using MRI, radiologists exhibit low specificity and significant inter-observer variability, leading to potential d…
Multimodal MRI-Ultrasound AI for Prostate Cancer Detection Outperforms Radiologist MRI Interpretation: A Multi-Center Study
Hassan Jahanandish, Shengtian Sang, Cynthia Xinran Li +6
Pre-biopsy magnetic resonance imaging (MRI) is increasingly used to target suspicious prostate lesions. This has led to artificial intelligence (AI) applications improving MRI-base…
ProsDectNet: Bridging the Gap in Prostate Cancer Detection via Transrectal B-mode Ultrasound Imaging
Sulaiman Vesal, Indrani Bhattacharya, Hassan Jahanandish +8
Interpreting traditional B-mode ultrasound images can be challenging due to image artifacts (e.g., shadowing, speckle), leading to low sensitivity and limited diagnostic accuracy.…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Correlated Feature Aggregation by Region Helps Distinguish Aggressive from Indolent Clear Cell Renal Cell Carcinoma Subtypes on CT
Karin Stacke, Indrani Bhattacharya, Justin R. Tse +3
Renal cell carcinoma (RCC) is a common cancer that varies in clinical behavior. Indolent RCC is often low-grade without necrosis and can be monitored without treatment. Aggressive…
Domain Generalization for Prostate Segmentation in Transrectal Ultrasound Images: A Multi-center Study
Sulaiman Vesal, Iani Gayo, Indrani Bhattacharya +7
Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion relies…
Bridging the gap between prostate radiology and pathology through machine learning
Indrani Bhattacharya, David S. Lim, Han Lin Aung +11
Prostate cancer is the second deadliest cancer for American men. While Magnetic Resonance Imaging (MRI) is increasingly used to guide targeted biopsies for prostate cancer diagnosi…
Weakly Supervised Registration of Prostate MRI and Histopathology Images
Wei Shao, Indrani Bhattacharya, Simon J. C. Soerensen +7
The interpretation of prostate MRI suffers from low agreement across radiologists due to the subtle differences between cancer and normal tissue. Image registration addresses this…
CorrSigNet: Learning CORRelated Prostate Cancer SIGnatures from Radiology and Pathology Images for Improved Computer Aided Diagnosis
Indrani Bhattacharya, Arun Seetharaman, Wei Shao +10
Magnetic Resonance Imaging (MRI) is widely used for screening and staging prostate cancer. However, many prostate cancers have subtle features which are not easily identifiable on…