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RespectKnowledge/README.md
  • 🔭 I’m currently working on Deep Learning and machine learning projects
  • 🌱 I’m currently learning semi or unsupervised methods for segmentation, classification
  • 👯 I’m looking to collaborate on research and projects for industery.

------------------------------ IEEE - ISBI 2023 2023 challenges contribution ------------------------------------------------

  • Edited Magnetic Resonance Spectroscopy Reconstruction Challenge (3rd position)
  • The Image Analysis for CTA Endovascular Stroke Therapy (IACTA-EST) Data Challenge (1st and 3rd position)
  • SMILE-UHURA : Small Vessel Segmentation at MesoscopIc ScaLEfrom Ultra-High ResolUtion 7T Magnetic Resonance Angiograms (3rd position)
  • SHINY-ICARUS: Segmentation over tHree dImensional rotational aNgiographY of Internal Carotid ArteRy with aneUrySm (5th position)

------------------------------ MICCAI 2022 challenges contribution ------------------------------------------------

  • CuRIOUS 2022 Segmentation Challenge (1st Position)
  • CMRxMotion challenge(4th position)
  • Multi-domain Cross-time-point Infant Cerebellum MRI Segmentation 2022 (cSeg-2022)(4th position)
  • Multi-site, Multi-Domain Airway Tree Modeling (ATM’22) (6th position)
  • The 2022 Intracranial Hemorrhage Segmentation Challenge on Non-Contrast head CT (NCCT) (9th position)
  • Ischemic Stroke Lesion Segmentation Challenge - ISLES'22(10th position)
  • Kidney PArsing Challenge 2022(Multi-Structure Segmentation for Renal Cancer Treatment) (11th position)
  • Pulmonary Artery Segmentation Challenge 2022 (16th position)

----------------------------------------------MICCAI 2021 challenges contribution---------------------------------------------------------------------

  • Challenge: Diabetic Foot Ulcer Challenge 2021 (4th position)

  • Challenge: FetReg 2021: Placental Vessel Segmentation and Registration in Fetoscopy(4th position)

  • Challenge: Foot Ulcer Segmentation Challenge 2021(5th position)

  • Challenge: MICCAI 2021 FLARE Challenge: Fast and Low GPU memory Abdominal oRgan sEgmentation(7th position)

  • Challenge: HEad and neCK TumOR (HECKTOR)segmentation and outcome prediction in PET/CT images 2021(14th position)

  • Challenge: Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI(10th position)

  • Challenge: Fetal Brain Tissue Annotation and Segmentation Challenge (Feta2021)(13th position)

  • Challenge: Chest XR COVID-19 detection (Grand challenge website)(6th position)

  • Challenge:AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge(13th position)

  • Challenge: KNIGHT Challenge (Kidney clinical Notes and Imaging to Guide and Help personalize Treatment and biomarkers discovery)(5th position)

  • 📫 How to reach me: [email protected]

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  1. EMIDEC-Challenge EMIDEC-Challenge Public

    Python 1

  2. LSTM-1DCNN-GRU-for-Depression LSTM-1DCNN-GRU-for-Depression Public

    Jupyter Notebook 13 4

  3. EEG_Speech_Depression_MultiDL EEG_Speech_Depression_MultiDL Public

    Jupyter Notebook 22 5

  4. ABIDE_Classification_DLModel ABIDE_Classification_DLModel Public

    Python 5 3

  5. FLARE_21_Segmentation_DL FLARE_21_Segmentation_DL Public

    Python 4

  6. EEG-using-deep-Learning EEG-using-deep-Learning Public

    In this Basic Tutorial, I have used 1DCNN for EEG classification using random dataset, You can use your own dataset

    Jupyter Notebook 18 1