Image segmentation of post-mortem computed tomography data in forensic imaging: Methods and applications

Ebert, Lars C.; Dobay, Akos; Franckenberg, Sabine; Thali, Mj.; Decker, Summer; Ford, Jonathan

doi:10.1016/j.fri.2021.200483

Cited by 9 publications

(4 citation statements)

References 55 publications

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“…The 3D visualizations derived from CT scanning serves as a valuable complementary tool for visualizing fractures and metal objects like projectiles, metal fragments and gunshot pellets (Figure 1). It also allows for 3D visualizations of bullet paths [28][29][30][31]. Precise measurements can be taken using these 3D models, such as in the case of a stab wound or the measurement of fracture height in the bones of the lower extremities (information used for estimating the height of the vehicle that hit the person).…”

Section: Three-dimensional Documentation Of the Body: Pmct Pmmr Surfa...mentioning

confidence: 99%

A Virtual, 3D Multimodal Approach to Victim and Crime Scene Reconstruction

Villa,

Lynnerup,

Jacobsen

2023

Diagnostics

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In the last two decades, forensic pathology and crime scene investigations have seen a rapid increase in examination tools due to the implementation of several imaging techniques, e.g., CT and MR scanning, surface scanning and photogrammetry. These tools encompass relatively simple visualization tools to powerful instruments for performing virtual 3D crime scene reconstructions. A multi-modality and multiscale approach to a crime scene, where 3D models of victims and the crime scene are combined, offers several advantages. A permanent documentation of all evidence in a single 3D environment can be used during the investigation phases (e.g., for testing hypotheses) or during the court procedures (e.g., to visualize the scene and the victim in a more intuitive manner). Advanced computational approaches to understand what might have happened during a crime can also be applied by, e.g., performing a virtual animation of the victim in the actual context, which can provide important information about possible dynamics during the event. Here, we present an overview of the different techniques and modalities used in forensic pathology in conjunction with crime scene investigations. Based on our experiences, the advantages and challenges of an image-based multi-modality approach will be discussed, including how their use may introduce new visualization modalities in court, e.g., virtual reality (VR) and 3D printing. Finally, considerations about future directions in research will be mentioned.

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Section: Three-dimensional Documentation Of the Body: Pmct Pmmr Surfa...mentioning

confidence: 99%

A Virtual, 3D Multimodal Approach to Victim and Crime Scene Reconstruction

Villa,

Lynnerup,

Jacobsen

2023

Diagnostics

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“…It was developed by Dr Kenney and Dr Eberhart in 1995, and it has been widely used as an optimization tool in areas including telecommunications, computer graphics, biological or medical science, signal processing, data mining, robotics, neural networks etc. [5]. The movement of the particles is influenced by two factors, the particle's best solution (pbest) and the global best solution found by all the particles (gbest), which influence the particle's velocity through the search space by creating an attractive force [23].…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

“…However, the degree of similarity between each pixel and each cluster would vary. The effectiveness of FCM significantly depends on the first cluster canters, which are challenging to identify [5,35,36].…”

Section: Fuzzy C-means Algorithm For Image Segmentationmentioning

confidence: 99%

“…These methods improved the quality and accuracy of the results while also cutting down on the computation time. Even though there have been hundreds of segmentation strategies documented in the literature and with the volume of image segmentation research growing, it might be challenging to choose the optimum segmented output measurement strategy for a certain type of image [4,5,6,7].…”

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Image segmentation-based optimization algorithms: A Review

Mohamed

Mahmoud²,

Hemeida³

2022

Aswan University Journal of Sciences and Technology

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Image segmentation is the division of a digital image into multiple subgroups of pixels known as Image Objects. This procedure can minimize the complexity of the image, making image analysis easier. Image Segmentation is one of the most crucial areas in computer vision and one of the oldest research questions. There are many useful applications of image processing such as image sharpening, blurring, grayscale conversion, and edges detection that can be utilized in different domains. Digital image processing employing neural networks has gained popularity recently because of the expansion of artificial intelligence algorithms and its ecosystem. It can be used in a wide range of industries, including security, banks, the military, agriculture, law enforcement, manufacturing, and medicine.

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Pediatric forensic postmortem computed tomography: basics to advanced

Gould,

Harty

2024

Pediatr Radiol

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Image segmentation of post-mortem computed tomography data in forensic imaging: Methods and applications

Cited by 9 publications

References 55 publications

A Virtual, 3D Multimodal Approach to Victim and Crime Scene Reconstruction

A Virtual, 3D Multimodal Approach to Victim and Crime Scene Reconstruction

Image segmentation-based optimization algorithms: A Review

Pediatric forensic postmortem computed tomography: basics to advanced

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