Staining blindly: an update on coloring techniques for fecal smears in parasitology: a scoping review

Dye application for parasite highlighting in the Ova and Parasite exam is a common practice in parasitology diagnosis. Methods: A scoping review investigated how staining solutions interact with parasite structures. After screening 1334 papers, 35 met eligibility criteria. Results: Differentiating background from foreground in the fecal smear under light microscopy is the core of the research on this topic. Refractivity, unevenness of staining, size and temperature were explored to enhance staining protocols. Cryptosporidium spp. and Microsporidia were the main studied species. Conclusion: Studies on diagnostic efficacy outperform those that elucidate the physical-chemical interaction between dyes and parasites. An alternative approach involves technicians using computational tools to reduce subjectivity in fecal smear interpretation, deviating from conventional methods.

Toward automating the diagnosis of gastrointestinal parasites in cats and dogs

Diagnosing gastrointestinal parasites by microscopy slide examination often leads to human interpretation errors, which may occur due to fatigue, lack of training and infrastructure, presence of artifacts (e.g., various types of cells, algae, yeasts), and other reasons. We have investigated the stages in automating the process to cope with the interpretation errors. This work presents advances in two stages focused on gastrointestinal parasites of cats and dogs: a new parasitological processing technique, named TF-Test VetPet, and a microscopy image analysis pipeline based on deep learning methods. TF-Test VetPet improves image quality by reducing cluttering (i.e., eliminating artifacts), which favors automated image analysis. The proposed pipeline can identify three species of parasites in cats and five in dogs, distinguishing them from fecal impurities with an average accuracy of 98,6%. We also make available the two datasets with images of parasites of dogs and cats, which were obtained by processing fecal smears with temporary staining using TF-Test VetPet.

TF-Test techniques for the laboratory diagnosis of gastrointestinal parasites of humans and animals

Intestinal parasites inhabit the intestinal tract of humans and animals, causing damages whose severity depends on several factors related to the parasite and the host. Immunocompromised individuals are more likely to develop severe forms of parasitic infestation. The diagnosis of the gastrointestinal parasitosis is mainly performed by the examination of the feces, which consists of the direct visualization and identification of the parasites eliminated through the feces. These tests are generally low sensitive and the microscope slides contain a large number of impurities, which can impair the result of the diagnosis. In order to improve the diagnostic accuracy, a new parasitological technique called Three Fecal Test (TF‑Test) was developed. To further improve its diagnostic accuracy, few modifications of the original protocols have been made with the years. In this study the performance of these new techniques to detect gastrointestinal parasites in human and animal fecal samples was described and discussed in relation to the performance of other conventional coprological tests. It could be concluded that the TF‑Test conventional and modified can be used for the diagnosis of several human and animal parasites, with satisfactory results.

Federated learning enables big data for rare cancer boundary detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Detection of intestinal parasites in human faecal samples using dissolved air flotation

OBJECTIVE

Ova and parasite (O&P) examination is recommended for the laboratory diagnosis of agents causing parasitic infections; however, this exam requires scientific and technological improvements to enhance its diagnostic validity. Dissolved air flotation (DAF) is an efficient technical principle separating suspended solids in a liquid medium. We aimed to develop and validate a new procedure for intestinal parasite detection with DAF.

METHODS

In this study, we collected samples from 500 volunteers, screened them by direct examination, and transferred the material to tubes using the Three Faecal Test (TF-Test) for triplicate DAF tests. We evaluated physical-chemical parameters and DAF prototype components through quantifying parasites recovered from floated and non-floated regions of the flotation column. The DAF operation protocol was validated with the gold standard results.

RESULTS

The 10% saturated volume proportion and cationic surfactant showed regularity and high parasite recovery (80%). Modifications of the needle device did not influence parasite recovery (p > 0.05). Sensitivity, specificity, accuracy and kappa agreement obtained with the DAF protocol were 91%, 100%, 93% and substantial (k = 0.64), respectively.

CONCLUSION

The DAF principle could be used to process faecal samples in routine laboratory exams, enabling intestinal parasite detection.

Dissolved air flotation as potential new mechanism for intestinal parasite diagnosis in feces

The parasitological examination of feces is recommended for the laboratory diagnosis of intestinal parasites due to its practicality, low-cost, and moderate diagnostic sensitivity. Dissolved Air Flotation (DAF) is an efficient technical principle used in other areas to separate dispersed solids. This study sought the preliminary evaluation of a proof-of-concept prototype as a tool for detecting species of parasites by adjusting DAF. Two DAF prototype units were developed to evaluate microbubbles' generation amidst fecal suspension and parasites' capture. For this evaluation, samples were screened and processed by the TF-Test technique (Control) and simultaneously by DAF device. The dimensional and attachment characteristics in the formation of the microbubbles were evaluated, and the percentage of parasitic recovery in floated and not-floated regions compared by Student's t-test. The second prototype unit proved to be more efficient in forming microbubbles with diameters between 34 and 170µm. The flotation tests showed a recovery of 73.27%, 58.12%, 37.85%, and 91.89% for Ascaris lumbricoides, Hymenolepis diminuta, Giardia duodenalis, and Strongyloides stercoralis, respectively. This study confirmed the selective interaction between microbubbles and parasite eggs and larvae during the flotation process using the DAF principle for the first time through imaging.

Automated Diagnostics: Advances in the Diagnosis of Intestinal Parasitic Infections in Humans and Animals

The increasingly close proximity between people and animals is of great concern for public health, given the risk of exposure to infectious diseases transmitted through animals, which are carriers of more than 60 zoonotic agents. These diseases, which are included in the list of Neglected Tropical Diseases, cause losses in countries with tropical and subtropical climates, and in regions with temperate climates. Indeed, they affect more than a billion people around the world, a large proportion of which are infected by one or more parasitic helminths, causing annual losses of billions of dollars. Several studies are being conducted in search for differentiated, more sensitive diagnostics with fewer errors. These studies, which involve the automated examination of intestinal parasites, still face challenges that must be overcome in order to ensure the proper identification of parasites. This includes a protocol that allows for elimination of most of the debris in samples, satisfactory staining of parasite structures, and a robust image database. Our objective here is therefore to offer a critical description of the techniques currently in use for the automated diagnosis of intestinal parasites in fecal samples, as well as advances in these techniques.

Automated diagnosis of intestinal parasites: A new hybrid approach and its benefits

Intestinal parasites are responsible for several diseases in human beings. In order to eliminate the error-prone visual analysis of optical microscopy slides, we have investigated automated, fast, and low-cost systems for the diagnosis of human intestinal parasites. In this work, we present a hybrid approach that combines the opinion of two decision-making systems with complementary properties: (DS₁) a simpler system based on very fast handcrafted image feature extraction and support vector machine classification and (DS₂) a more complex system based on a deep neural network, Vgg-16, for image feature extraction and classification. DS₁ is much faster than DS₂, but it is less accurate than DS₂. Fortunately, the errors of DS₁ are not the same of DS₂. During training, we use a validation set to learn the probabilities of misclassification by DS₁ on each class based on its confidence values. When DS₁ quickly classifies all images from a microscopy slide, the method selects a number of images with higher chances of misclassification for characterization and reclassification by DS₂. Our hybrid system can improve the overall effectiveness without compromising efficiency, being suitable for the clinical routine - a strategy that might be suitable for other real applications. As demonstrated on large datasets, the proposed system can achieve, on average, 94.9%, 87.8%, and 92.5% of Cohen's Kappa on helminth eggs, helminth larvae, and protozoa cysts, respectively.

A historical review of the techniques of recovery of parasites for their detection in human stools

Since the early 20th century, the detection of intestinal parasites has improved with the development of several techniques for parasitic structures recovery and identification, which differ in sensitivity, specificity, practicality, cost, and infrastructure demand. This study aims to review, in chronological order, the stool examination techniques and discuss their advantages, limitations, and perspectives, and to provide professionals and specialists in this field with data that lays a foundation for critical analysis on the use of such procedures. The concentration procedures that constitute the main techniques applied in routine research and in parasitological kits are a) spontaneous sedimentation; b) centrifugation-sedimentation with formalin-ethyl acetate; and c) flotation with zinc sulfate solution. While selecting a technique, one should consider the purpose of its application and the technical-operational, biological, and physicochemical factors inherent in the procedures used in stool processing, which may restrict its use. These intrinsic limitations may have undergone procedural changes driven by scientific and technological development and by development of alternative methods, which now contribute to the improvement of diagnostic accuracy.

Use of the aqueous biphasic system as an alternative for concentration of Ascaris lumbricoides eggs, with non-toxic separation of faecal residues and fats

OBJECTIVES

Human enteroparasites are considered a serious public health problem in underdeveloped countries located in world regions with tropical, subtropical and equatorial climates. These parasites are commonly diagnosed by the Parasitological Examination of Faeces (PEF), performed by conventional techniques and/or commercial kits that result in tests with low-to-moderate sensitivity, due to the use of destructive chemical solvents to parasite structures, and to present excess adipose substance and digestive residues in their microscopic slides. In order to improve the efficacy of these tests/examinations, this study aimed to investigate a new alternative for the PEF, with the use of Aqueous Biphasic System (ABS).

METHODS

For this, four ABSs containing poly (ethylene glycol), PEG (PEG-4000 and PEG-6000), dipotassium phosphate and sodium citrate at different concentrations in the biphasic systems were evaluated with faecal samples containing eggs of Ascaris lumbricoides.

RESULTS

The ABS consisting of PEG-4000 and dipotassium phosphate, at concentrations of 55% w/w and 20% w/w, respectively, achieved 100% satisfactory results compared to the conventional TF-Test technique in terms of preservation and concentration of A. lumbricoides eggs, with adequate separation of digestive residues, without using a centrifuge or chemical solvents that may cause harm to the parasites.

CONCLUSIONS

This study presents ABS as a new low-cost technical principle for the detection of parasite eggs in PEF. The new technique is simple, fast, non-toxic, not harmful to the parasite and does not require a centrifuge.

The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease

A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neurodegenerative disorders. Recent works show that such biomarkers can be obtained by image analysis techniques. However, these techniques cannot be directly compared since they use different databases and validation protocols. In this paper, we present an extensive study of image descriptors for the diagnosis of Alzheimer Disease (AD) and introduce a new one, named Residual Center of Mass (RCM). The RCM descriptor explores image moments and other techniques to enhance brain regions and select discriminative features for the diagnosis of AD. For validation, a Support Vector Machine (SVM) is trained with the selected features to classify images from normal subjects and patients with AD. We show that RCM with SVM achieves the best accuracies on a considerable number of exams by 10-fold cross-validation - 95.1% on 507 FDG-PET scans and 90.3% on 1374 MRI scans.

Comparative study of five techniques for the diagnosis of canine gastrointestinal parasites

Differences in the efficacy of diagnostic techniques employed in the parasitological examination of feces are a limiting factor of this laboratory procedure in the field of Veterinary Parasitology. To verify advances in this type of examination in dogs, we conducted a study using a new technique (TFGII/Dog). Fifty naturally infected dogs were housed in individual stalls, and their feces were evaluated comparatively using this technique and four other conventional techniques. The TFGII/Dog showed high levels of sensitivity and efficiency, surpassing the diagnostic accuracy of the other techniques with a kappa concordance index of 0.739 (Substantial), as opposed to 0.546 (Moderate), 0.485 (Moderate), 0.467 (Moderate), and 0.325 (Fair) of the Spontaneous-Sedimentation, Centrifugal-Flotation in Saturated Zinc Sulfate Solution, Centrifugal-Flotation in Saturated Sugar Solution, and Spontaneous-Flotation in Saturated Sodium Chloride Solution techniques, respectively. The combination of positive results of all techniques comprises eight genera of parasites, with Ancylostoma spp. predominating among helminths, and Cystoisospora spp. among protozoa. The TFGII/Dog technique showed better diagnostic performance, and can therefore be considered an important tool for optimizing the results of laboratory routines and for the control of canine gastrointestinal parasites.

Validation of a new technique to detect Cryptosporidium spp. oocysts in bovine feces

Due to its important zoonotic potential, cryptosporidiosis arouses strong interest in the scientific community, because, it was initially considered a rare and opportunistic disease. The parasitological diagnosis of the causative agent of this disease, the protozoan Cryptosporidium spp., requires the use of specific techniques of concentration and permanent staining, which are laborious and costly, and are difficult to use in routine laboratory tests. In view of the above, we conducted the feasibility, development, evaluation and intralaboratory validation of a new parasitological technique for analysis in optical microscopy of Cryptosporidium spp. oocysts, called TF-Test Coccidia, using fecal samples from calves from the city of Araçatuba, São Paulo. To confirm the aforementioned parasite and prove the diagnostic efficiency of the new technique, we used two established methodologies in the scientific literature: parasite concentration by centrifugal sedimentation and negative staining with malachite green (CSN-Malachite) and Nested-PCR. We observed good effectiveness of the TF-Test Coccidia technique, being statistically equivalent to CSN-Malachite. Thus, we verified the effectiveness of the TF-Test Coccidia parasitological technique for the detection of Cryptosporidium spp. oocysts and observed good concentration and morphology of the parasite, with a low amount of debris in the fecal smear.

HIGH PREVALENCE OF Blastocystis spp. INFECTION IN CHILDREN AND STAFF MEMBERS ATTENDING PUBLIC URBAN SCHOOLS IN SÃO PAULO STATE, BRAZIL

After a gastroenteritis outbreak of unknown etiology in the municipality of Sebastião da Grama, SãoPaulo, Brazil, we conducted a parasitological survey to establish the epidemiological profile of enteroparasitosis in children and staff members attending the public urban schools in operation in town. The cross-sectional study evaluated 172 children aged 11 months to 6 years old and 33 staff members aged 19 to 58 years old. Overall, 96 (55.81%) children and 20 (60.61%) staff members were mono-parasitized, while 58 (33.72%) children and 4 (12.12%) workers were poly-parasitized. Protozoa (88.37%; 72.73%) was more prevalent than helminthes (3.48%; 0%) in children and staff members respectively.Blastocystis spp. was the most prevalent parasite in children (86.63%) and staff members (66.67%). The age of 1 year old or less was found to be associated with increased prevalence of giardiasis [OR = 13.04; 95%CI 2.89-58.91; p = 0.00] and public garbage collection was identified as a protective factor against intestinal helminth infections [OR = 0.06; 95%CI 0.00-0.79; p = 0.03]. Although most of the children tested positive for Blastocystis spp. and also presented clinical signs/symptoms (62.2%), this association was not statistically significant [OR = 1.35; 95%CI 0.53-3.44; p = 0.51]. Intestinal parasites still represent a public health concern and this study underscores the importance of further investigations to better understand the pathogenic role of Blastocystis spp.

Evolving technologies for growing, imaging and analyzing 3D root system architecture of crop plants

A plant's ability to maintain or improve its yield under limiting conditions, such as nutrient deficiency or drought, can be strongly influenced by root system architecture (RSA), the three-dimensional distribution of the different root types in the soil. The ability to image, track and quantify these root system attributes in a dynamic fashion is a useful tool in assessing desirable genetic and physiological root traits. Recent advances in imaging technology and phenotyping software have resulted in substantive progress in describing and quantifying RSA. We have designed a hydroponic growth system which retains the three-dimensional RSA of the plant root system, while allowing for aeration, solution replenishment and the imposition of nutrient treatments, as well as high-quality imaging of the root system. The simplicity and flexibility of the system allows for modifications tailored to the RSA of different crop species and improved throughput. This paper details the recent improvements and innovations in our root growth and imaging system which allows for greater image sensitivity (detection of fine roots and other root details), higher efficiency, and a broad array of growing conditions for plants that more closely mimic those found under field conditions.

TF-Test Modified: New Diagnostic Tool for Human Enteroparasitosis

Intestinal parasitosis is highly prevalent worldwide, being among the main causes of illness and death in humans. Currently, laboratory diagnosis of the intestinal parasites is accomplished through manual technical procedures, mostly developed decades ago, which justifies the development of more sensitive and practical techniques. Therefore, the main objective of this study was to develop, evaluate, and validate a new parasitological technique referred to as TF-Test Modified, in comparison to three conventional parasitological techniques: TF-Test Conventional; Rugai, Mattos & Brisola; and Helm Test/Kato-Katz. For this realization, we collected stool samples from 457 volunteers located in endemic areas of Campinas, São Paulo, Brazil, and statistically compared the techniques. Intestinal protozoa and helminths were detected qualitatively in 42.23% (193/457) of the volunteers by TF-Test Modified technique, against 36.76% (168/457) by TF-Test Conventional, 5.03% (23/457) by Helm Test/Kato-Katz, and 4.16% (19/457) by Rugai, Mattos & Brisola. Furthermore, the new technique presented "almost perfect kappa" agreement in all evaluated parameters with 95% (P < 0.05) of estimation. The current study showed that the TF-Test Modified technique can be comprehensively used in the diagnosis of intestinal protozoa and helminths, and its greater diagnostic sensitivity should help improving the quality of laboratory diagnosis, population surveys, and control of intestinal parasites.

A new laboratorial method for the diagnosis of gastrointestinal parasites in dogs

In this study, we aimed to introduce a new technique called TF-Test Modified∕Dog for the diagnosis of gastrointestinal parasites in dogs. Fecal samples from 106 dogs were processed by the technique TF-Test Modified∕Dog and the techniques of centrifugation-flotation in zinc sulfate, simple-flotation by saturated solution of sodium chloride, direct microscopy exam and TF-Test Conventional. Sensitivity was higher in the TF-Test Modified∕Dog (98.41%), followed by flotation in saturated zinc sulfate (77.78%), TF-Test Conventional (73.02%), flotation by saturated sodium chloride (55.55%), and direct microscopy exam (30.16%). The diagnostic efficiency varied from 58.49% to 99.06%, with the highest value also obtained by the new proposed technique. Efficiency level of 99.06% with kappa index 0.979 (almost perfect) was obtained with the TF-Test Modified∕Dog. These results represent significant statistical gains (P < 0.05) of 20.63% in sensitivity and 12.27% in efficiency over the best among the other techniques - flotation by saturated zinc sulfate, whose kappa index was 0.738, much lower than that of the TF-Test Modified∕Dog. All techniques presented 100% specificity. In this sense, the high sensitivity of the TF-Test Modified∕Dog makes it suitable for epidemiological surveys of gastrointestinal parasitosis in dogs, zoonoses control and preventive surveillance programs.

Hybrid approaches for interactive image segmentation using the live markers paradigm

Interactive image segmentation methods normally rely on cues about the foreground imposed by the user as region constraints (markers/brush strokes) or boundary constraints (anchor points). These paradigms often have complementary strengths and weaknesses, which can be addressed to improve the interactive experience by reducing the user’s effort. We propose a novel hybrid paradigm based on a new form of interaction called live markers, where optimum boundary-tracking segments are turned into internal and external markers for region-based delineation to effectively extract the object. We present four techniques within this paradigm: 1) LiveMarkers; 2) RiverCut; 3) LiveCut; and 4) RiverMarkers. The homonym LiveMarkers couples boundary-tracking via live-wire-on-the-fly (LWOF) with optimum seed competition by the image foresting transform (IFT-SC). The IFT-SC can cope with complex object silhouettes, but presents a leaking problem on weaker parts of the boundary that is solved by the effective live markers produced by LWOF. Conversely, in RiverCut, the long boundary segments computed by Riverbed around complex shapes provide markers for Graph Cuts by the Min-Cut/Max-Flow algorithm (GCMF) to complete segmentation on poorly defined sections of the object’s border. LiveCut and RiverMarkers further demonstrate that live markers can improve segmentation even when the combined approaches are not complementary (e.g., GCMFs shrinking bias is also dramatically prevented when using it with LWOF). Moreover, since delineation is always region based, our methodology subsumes both paradigms, representing a new way of extending boundary tracking to the 3D image domain, while speeding up the addition of markers close to the object’s boundary-a necessary but time consuming task when done manually. We justify our claims through an extensive experimental evaluation on natural and medical images data sets, using recently proposed robot users for boundary-tracking methods.

Riverbed: a novel user-steered image segmentation method based on optimum boundary tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

A 3D generalization of user-steered live-wire segmentation

We have been developing user-steered image segmentation methods for situations which require considerable human assistance in object definition. In the past, we have presented two paradigms, referred to as live-wire and live-lane, for segmenting 2D/3D/4D object boundaries in a slice-by-slice fashion, and demonstrated that live-wire and live-lane are more repeatable, with a statistical significance level of P < 0.03, and are 1.5-2.5 times faster, with a statistical significance level of P < 0.02, than manual tracing. In this paper, we introduce a 3D generalization of the live-wire approach for segmenting 3D/4D object boundaries which further reduces the time spent by the user in segmentation. In a 2D live-wire, given a slice, for two specified points (pixel vertices) on the boundary of the object, the best boundary segment is the minimum-cost path between the two points, described as a set of oriented pixel edges. This segment is found via Dijkstra's algorithm as the user anchors the first point and moves the cursor to indicate the second point. A complete 2D boundary is identified as a set of consecutive boundary segments forming a "closed", "connected", "oriented" contour. The strategy of the 3D extension is that, first, users specify contours via live-wiring on a few slices that are orthogonal to the natural slices of the original scene. If these slices are selected strategically, then we have a sufficient number of points on the 3D boundary of the object to subsequently trace optimum boundary segments automatically in all natural slices of the 3D scene. A 3D object boundary may define multiple 2D boundaries per slice. The points on each 2D boundary form an ordered set such that when the best boundary segment is computed between each pair of consecutive points, a closed, connected, oriented boundary results. The ordered set of points on each 2D boundary is found from the way the users select the orthogonal slices. Based on several validation studies involving segmentation of the bones of the foot in MR images, we found that the 3D extension of live-wire is more repeatable, with a statistical significance level of P < 0.0001, and 2-6 times faster, with a statistical significance level of P < 0.01, than the 2D live-wire method, and 3-15 times faster than manual tracing.

An ultra-fast user-steered image segmentation paradigm: live wire on the fly

We have been developing general user steered image segmentation strategies for routine use in applications involving a large number of data sets. In the past, we have presented three segmentation paradigms: live wire, live lane, and a three-dimensional (3-D) extension of the live-wire method. In this paper, we introduce an ultra-fast live-wire method, referred to as live wire on the fly, for further reducing user's time compared to the basic live-wire method. In live wire, 3-D/four-dimensional (4-D) object boundaries are segmented in a slice-by-slice fashion. To segment a two-dimensional (2-D) boundary, the user initially picks a point on the boundary and all possible minimum-cost paths from this point to all other points in the image are computed via Dijkstra's algorithm. Subsequently, a live wire is displayed in real time from the initial point to any subsequent position taken by the cursor. If the cursor is close to the desired boundary, the live wire snaps on to the boundary. The cursor is then deposited and a new live-wire segment is found next. The entire 2-D boundary is specified via a set of live-wire segments in this fashion. A drawback of this method is that the speed of optimal path computation depends on image size. On modestly powered computers, for images of even modest size, some sluggishness appears in user interaction, which reduces the overall segmentation efficiency. In this work, we solve this problem by exploiting some known properties of graphs to avoid unnecessary minimum-cost path computation during segmentation. In live wire on the fly, when the user selects a point on the boundary the live-wire segment is computed and displayed in real time from the selected point to any subsequent position of the cursor in the image, even for large images and even on low-powered computers. Based on 492 tracing experiments from an actual medical application, we demonstrate that live wire on the fly is 1.3-31 times faster than live wire for actual segmentation for varying image sizes, although the pure computational part alone is found to be about 120 times faster.