14 citations · 22 across the 8 of their papers we have counts for
10 papers
Large-Scale Pretraining for Improving Deep Learning-Based Geometric Distortion Correction of Diffusion-Weighted Imaging
Saroj Khanal, Yashawant Kumar Yadav, Kritam Bhattarai +12
Diffusion-weighted imaging (DWI) is widely used in clinical settings but remains vulnerable to geometric distortion. Conventional correction methods often require additional acquis…
Training Beyond Convergence: Grokking nnU-Net for Glioma Segmentation in Sub-Saharan MRI
Mohtady Barakat, Omar Salah, Ahmed Yasser +8
Gliomas are placing an increasingly clinical burden on Sub-Saharan Africa (SSA). In the region, the median survival for patients remains under two years, and access to diagnostic i…
Resource-Efficient Glioma Segmentation on Sub-Saharan MRI
Freedmore Sidume, Oumayma Soula, Joseph Muthui Wacira +10
Gliomas are the most prevalent type of primary brain tumors, and their accurate segmentation from MRI is critical for diagnosis, treatment planning, and longitudinal monitoring. Ho…
Brain Tumor Segmentation in Sub-Sahara Africa with Advanced Transformer and ConvNet Methods: Fine-Tuning, Data Mixing and Ensembling
Toufiq Musah, Chantelle Amoako-Atta, John Amankwaah Otu +21
Brain tumors are among the deadliest cancers worldwide, with particularly devastating impact in Sub-Saharan Africa (SSA) where limited access to medical imaging infrastructure and…
Deep Ensemble approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings
Jeremiah Fadugba, Isabel Lieberman, Olabode Ajayi +6
Segmentation of brain tumors is a critical step in treatment planning, yet manual segmentation is both time-consuming and subjective, relying heavily on the expertise of radiologis…
Generative Style Transfer for MRI Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan Africa
Rancy Chepchirchir, Jill Sunday, Raymond Confidence +5
In Sub-Saharan Africa (SSA), the utilization of lower-quality Magnetic Resonance Imaging (MRI) technology raises questions about the applicability of machine learning methods for c…
Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma Dataset
Bijay Adhikari, Pratibha Kulung, Jakesh Bohaju +6
Automating brain tumor segmentation using deep learning methods is an ongoing challenge in medical imaging. Multiple lingering issues exist including domain-shift and applications…
Automatic Medical Report Generation: Methods and Applications
Li Guo, Anas M. Tahir, Dong Zhang +2
The increasing demand for medical imaging has surpassed the capacity of available radiologists, leading to diagnostic delays and potential misdiagnoses. Artificial intelligence (AI…
On the Temperature of Machine Learning Systems
Dong Zhang
We develop a thermodynamic theory for machine learning (ML) systems. Similar to physical thermodynamic systems which are characterized by energy and entropy, ML systems possess the…
Towards SAMBA: Segment Anything Model for Brain Tumor Segmentation in Sub-Sharan African Populations
Mohannad Barakat, Noha Magdy, Jjuuko George William +4
Gliomas, the most prevalent primary brain tumors, require precise segmentation for diagnosis and treatment planning. However, this task poses significant challenges, particularly i…