Ines Njeh

21 papers C 1Misc 10Journal 9Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
An accurate framework based on transformer networks for breast cancer classification using histopathological image.
Netw. Model. Anal. Health Informatics Bioinform.
Marwa Naas, Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima
2025 J jnl
An explainable AI for breast cancer classification using vision Transformer (ViT).
Biomed. Signal Process. Control.
Marwa Naas, Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima
2025 J jnl
Deep learning based computer aided diagnosis (CAD) tool supported by explainable artificial intelligence for breast cancer exploration.
Appl. Intell.
Marwa Naas, Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima
2025 J jnl
Vision transformers (ViT) and deep convolutional neural network (D-CNN)-based models for MRI brain primary tumors images multi-classification supported by explainable artificial intelligence (XAI).
Vis. Comput.
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Nouha Farhat, Chokri Mhiri
2024 Misc conf
Review of MRI brain tumor segmentation and MGMT promoter classification methods on BraTs dataset based on Deep learning.
ATSIP
Feriel Amor, Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima
2023 C conf
Deep Transfer Learning (DTL) Based-Framework for an Accurate Multi-classification of MRI Brain Tumors.
CW
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Nouha Farhat, Chokri Mhiri
2023 J jnl
Deep efficient-nets with transfer learning assisted detection of COVID-19 using chest X-ray radiology imaging.
Multim. Tools Appl.
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Ahmed BenHamida
2022 Misc conf
Computer Aided Diagnosis (CAD) tool for MS lesions exploration In multimodal brain MRI.
ATSIP
Marwa Nass, Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Ahmed BenHamida
2022 Misc conf
Review of Computer Aided-Diagnosis (CAD) Systems for MRI Gliomas brain tumors explorations based on Machine Learning and Deep learning.
ATSIP
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Ahmed Ben Hamida
2021 J jnl
Deep Convolutional Encoder-Decoder algorithm for MRI brain reconstruction.
Medical Biol. Eng. Comput.
Ines Njeh, Hiba Mzoughi, Mohamed Ben Slima, Ahmed Ben Hamida, Chokri Mhiri, Kheireddine Ben Mahfoudh
2021 J jnl
Towards a computer aided diagnosis (CAD) for brain MRI glioblastomas tumor exploration based on a deep convolutional neuronal networks (D-CNN) architectures.
Multim. Tools Appl.
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Ahmed Ben Hamida, Chokri Mhiri, Kheireddine Ben Mahfoudh
2020 J jnl
Deep Multi-Scale 3D Convolutional Neural Network (CNN) for MRI Gliomas Brain Tumor Classification.
J. Digit. Imaging
Hiba Mzoughi, Ines Njeh, Ali Wali, Mohamed Ben Slima, Ahmed Ben Hamida, Chokri Mhiri, Kharedine Ben Mahfoudhe
2020 Misc conf
Glioblastomas brain Tumor Segmentation using Optimized U-Net based on Deep Fully Convolutional Networks (D-FCNs).
ATSIP
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Ahmed Ben Hamida
2018 Misc conf
Histogram equalization-based techniques for contrast enhancement of MRI brain Glioma tumor images: Comparative study.
ATSIP
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Ahmed Ben Hamida
2016 Misc conf
An automated MRI brain tissue segmentation approach.
ATSIP
Zaineb Ben Messaoud, Siwar Chnitti, Ines Njeh
2015 J jnl
3D multimodal MRI brain glioma tumor and edema segmentation: A graph cut distribution matching approach.
Comput. Medical Imaging Graph.
Ines Njeh, Lamia Sallemi, Ismail Ben Ayed, Khalil Chtourou, Stéphane Lehéricy, Damien Galanaud, Ahmed Ben Hamida
2014 Misc conf
A computer aided diagnosis 'CAD' for brain glioma exploration.
ATSIP
Ines Njeh, Lamia Sallemi, Mohamed Ben Slima, Ahmed Ben Hamida, Stéphane Lehéricy, Damien Galanaud
2014 Misc conf
Automatic brain MR perfusion image segmentation using adaptive diffusion flow active contours based on Modified Fuzzy C Means.
ATSIP
Abdelkhalek Bakkari, Ezzedine Ben Braiek, Ines Njeh, Ahmed Ben Hamida
2014 Misc conf
Automatic localization methodology dedicated to brain tumors based on ICP matching by using axial MRI symmetry.
ATSIP
Fatma Gargouri, Ines Njeh, Ahmed Ben Hamida, Khalil Chtourou
2014 Misc conf
Brief review of multiple sclerosis lesions segmentation methods on conventional magnetic resonance imaging.
ATSIP
Olfa Ghribi, Ines Njeh, Ahmed Ben Hamida, Wassim Zouch, Chokri Mhiri
2012 — conf
A distribution-matching approach to MRI brain tumor segmentation.
ISBI
Ines Njeh, Ismail Ben Ayed, Ahmed Ben Hamida
edge-cases.md
← Index edge-cases.md markdown 
# Edge Cases Samples
This is a list of samples that represent some edge cases where the extractors fail (completely or in part) to parse information we know to be there

**Sample:**

**VT:**

**Description:**

**Other:**


## PE Samples
### DotNET
**Sample:** `"/Users/p4c0/_samples/test-unzipped/98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7"`

**VT:** https://www.virustotal.com/gui/file/98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7/details

**Description:**
It is recognized as dotnet but it fails to extract any information, returning an empty dictionary:
```
{
    "sha256": "98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7",
    "md5": "a32eca5321baaf3d9b62ed129458a814",
    "sha1": "4524e99a3849c815a48579fb916e53cded739f46",
    "dotnet": {
        "Event" : [],
        "ExternalUnmanagedMethods" : [],
        "ExternalUnmanagedModules" : [],
        "ManifestResource" : [],
        "Resources" : []
    },
    "analysis_date": "2025-01-22 13:16:20.897"
}
```

with the following errors:
```
2025-01-22 14:16:20,896 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Format error dotnet file 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 Full error : 'CLR header of file is most likely corrupt.'
98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting metadata tables for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'existent_metadata_tables'
2025-01-22 14:16:20,896 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error extracting GUID for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'guid_stream_guids'
2025-01-22 14:16:20,896 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting CLR version for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'get_runtime_target_version'
2025-01-22 14:16:20,896 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting module info for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'metadata_table_exists'
2025-01-22 14:16:20,896 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting basic properties for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'info'
2025-01-22 14:16:20,897 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting assembly flags for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'clr_header'
2025-01-22 14:16:20,897 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting more metadata/info clr header for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'get_number_of_streams'
2025-01-22 14:16:20,897 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting streams for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'get_stream_names'
2025-01-22 14:16:20,897 - 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7 - ERROR - Error getting resources for 98eca73a0e33a41a72ac55c4bd0a75e5c83fdc3de382d031346045105cdf10e7: 'NoneType' object has no attribute 'has_resources'
```
**Other:**