8 citations · 15 across the 13 of their papers we have counts for
5 papers · 1 filter
TMSS: An End-to-End Transformer-based Multimodal Network for Segmentation and Survival Prediction
Numan Saeed, Ikboljon Sobirov, Roba Al Majzoub +1
When oncologists estimate cancer patient survival, they rely on multimodal data. Even though some multimodal deep learning methods have been proposed in the literature, the majorit…
Super Images -- A New 2D Perspective on 3D Medical Imaging Analysis
Ikboljon Sobirov, Numan Saeed, Mohammad Yaqub
In medical imaging analysis, deep learning has shown promising results. We frequently rely on volumetric data to segment medical images, necessitating the use of 3D architectures,…
An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data
Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov +1
Accurate prognosis of a tumor can help doctors provide a proper course of treatment and, therefore, save the lives of many. Traditional machine learning algorithms have been eminen…
Object Detection in Aerial Images: What Improves the Accuracy?
Hashmat Shadab Malik, Ikboljon Sobirov, Abdelrahman Mohamed
Object detection is a challenging and popular computer vision problem. The problem is even more challenging in aerial images due to significant variation in scale and viewpoint in…
Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?
Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi +1
Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are…